Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-18T19:19:36.427337Z
Paper Citation Record · LEDGER
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
As of 5 August 2026, this Paper Citation Record lists 100 of 299 outbound references and 64 inbound Pith citation observations for arXiv:2509.02547.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T13:31:24.753889Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-10T12:15:01.137692Z
Reference resolution
100 of 299 outbound references displayed
- verified exact55
- verified fuzzy30
- unresolved2
- parse uncertain0
- malformed identifier2
- metadata mismatch11
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 2396945c-eabb-4b66-8703-39135f8b1aa8 · outbound
This paper cites Proximal Policy Optimization Algorithms.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Proximal Policy Optimization Algorithms
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.870824Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4bcdb4dc-b734-4cba-943e-6a221710b7ae · outbound
This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.884172Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f7ec9216-8168-4138-9a66-00fde475356e · outbound
This paper cites Playing Atari with Deep Reinforcement Learning.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Playing Atari with Deep Reinforcement Learning
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.866403Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 51a38e8c-fdb4-48a4-8ea7-c7a11221d4f4 · outbound
This paper cites A Technical Survey of Reinforcement Learning Techniques for Large Language Models.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey A Technical Survey of Reinforcement Learning Techniques for Large Language Models
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-07-07T02:18:25.553364Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c802a854-f512-4e56-88f1-ed39a82c88db · outbound
This paper cites Reinforcement Learning Enhanced LLMs: A Survey.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Reinforcement Learning Enhanced LLMs: A Survey
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.875324Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 445e3597-d01a-4a9f-a365-cb6b197d9ec1 · outbound
This paper cites Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Enhancing Code LLMs with Reinforcement Learning in Code Generation: A Survey
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.880055Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation dd1c919c-db40-48e9-bcb8-04eb7bfcfba3 · outbound
This paper cites Survey on large language model-enhanced reinforcement learning: Concept, taxonomy, and methods.IEEE Transactions on Neural Networks and Learning Systems, 36(6):9737–9757, June 2025.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Survey on large language model-enhanced reinforcement learning: Concept, taxonomy, and methods.IEEE Transactions on Neural Networks and Learning Systems, 36(6):9737–9757, June 2025
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:46.766902Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 974982fd-1f54-4684-bc3f-518d10cee338 · outbound
This paper cites Synthetic Data RL: Task Definition Is All You Need.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Synthetic Data RL: Task Definition Is All You Need
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.858237Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8f97174b-0ea6-4fa5-8474-fd875a94a3fb · outbound
This paper cites Let large language models find the data to train themselves.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Let large language models find the data to train themselves
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.164052Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation df887682-effa-49cc-926f-47e4e88480b0 · outbound
This paper cites Reinforcement Pre-Training.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Reinforcement Pre-Training
Reference 10
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-18T19:21:48.478904Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 82991100-669e-4fa7-8439-456414022799 · outbound
This paper cites Inference-aware fine-tuning for best- of-n sampling in large language models.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Inference-aware fine-tuning for best- of-n sampling in large language models
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.439072Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 520c1980-21ef-4703-a46c-c65d147549b2 · outbound
This paper cites A survey of reinforcement learning in large language models: From data generation to test-time inference.Available at SSRN 5128927.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey A survey of reinforcement learning in large language models: From data generation to test-time inference.Available at SSRN 5128927
Reference 12
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.442376Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 38cb5da6-4859-467e-ba09-a95700d73bad · outbound
This paper cites Training language models to follow instructions with human feedback.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Training language models to follow instructions with human feedback
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.445626Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation fd962b78-169e-4c63-8873-44cb2333d49d · outbound
This paper cites Reinforcement Learning for LLM Post-Training: A Survey.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Reinforcement Learning for LLM Post-Training: A Survey
Reference 14
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-18T19:21:48.376249Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 53a7ab6b-16a0-4246-bd5b-83e320dda34c · outbound
This paper cites A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey A Comprehensive Survey of Direct Preference Optimization: Datasets, Theories, Variants, and Applications
Reference 15
- Resolution
- verified exact
- arxiv_id, observed 2026-06-10T02:11:10.714292Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 30828b37-65b1-424b-8307-cf32756ce4e1 · outbound
This paper cites Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Multilingual Knowledge Graph Completion with Self-Supervised Adaptive Graph Alignment
Reference 16
- Resolution
- malformed identifier
- doi_truncated, observed 2026-05-18T19:21:46.662487Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6fd84143-8792-4eaa-9dc3-3467e62e2971 · outbound
This paper cites Position: Agent Should Invoke External Tools ONLY When Epistemically Necessary.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Position: Agent Should Invoke External Tools ONLY When Epistemically Necessary
Reference 17
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.390112Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation be03dfa9-3240-45d1-952c-b28b3cf9a009 · outbound
This paper cites From System 1 to System 2: A Survey of Reasoning Large Language Models.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey From System 1 to System 2: A Survey of Reasoning Large Language Models
Reference 18
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.426898Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cc284fdc-decd-4222-9ecd-6c6fd5b7dd91 · outbound
This paper cites Large Language Model Agent: A Survey on Methodology, Applications and Challenges.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Large Language Model Agent: A Survey on Methodology, Applications and Challenges
Reference 19
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-18T19:21:46.673527Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 22dfb8e0-5607-4f3f-b478-cba99185768d · outbound
This paper cites van Duijn, Niki Stein, Mike Preuss, Peter van der Putten, and Kees Joost Batenburg.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey van Duijn, Niki Stein, Mike Preuss, Peter van der Putten, and Kees Joost Batenburg
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:46.743137Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7908cbc2-eb3d-4f6d-9e2a-f0bbce367f94 · outbound
This paper cites A review of prominent paradigms for LLM-based agents: Tool use, planning (including RAG), and feedback learning.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey A review of prominent paradigms for LLM-based agents: Tool use, planning (including RAG), and feedback learning
Reference 21
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.429687Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 96eb9ba1-e214-48e8-b858-4b0597943900 · outbound
This paper cites What are tools anyway? a survey from the language model perspective.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey What are tools anyway? a survey from the language model perspective
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.423529Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a7d74a82-9516-472f-be0d-43028de24e20 · outbound
This paper cites The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey The Landscape of Emerging AI Agent Architectures for Reasoning, Planning, and Tool Calling: A Survey
Reference 23
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.613347Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8de79810-8874-492d-9ce7-aa077060f9c8 · outbound
This paper cites an unresolved cited work.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Unresolved cited work
Reference 24
- Resolution
- unresolved
- raw_fallback, observed 2026-05-18T19:22:50.420467Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 01aa4e0f-97c6-45a0-87d8-ecb1612155ec · outbound
This paper cites A Survey on Self-Evolution of Large Language Models.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey A Survey on Self-Evolution of Large Language Models
Reference 25
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-18T19:21:48.350622Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b2532011-c579-4698-82fe-57b4dcb69540 · outbound
This paper cites LLMs Working in Harmony: A Survey on the Technological Aspects of Building Effective LLM-Based Multi Agent Systems.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey LLMs Working in Harmony: A Survey on the Technological Aspects of Building Effective LLM-Based Multi Agent Systems
Reference 26
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.246164Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9ec266e8-7f25-4a82-b1e8-27c581965ef1 · outbound
This paper cites Agent AI: Surveying the Horizons of Multimodal Interaction.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Agent AI: Surveying the Horizons of Multimodal Interaction
Reference 27
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:46.719040Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4876a34b-7f0a-4df9-9596-17a9f86843cb · outbound
This paper cites Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems
Reference 28
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-18T19:21:46.618753Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4fcfd900-328a-435f-a8a1-afc240977055 · outbound
This paper cites Multi-agent reinforcement learning: A comprehensive survey.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Multi-agent reinforcement learning: A comprehensive survey
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.426645Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7a445999-f65f-4c74-8227-913d327376e2 · outbound
This paper cites Multi-agent Reinforcement Learning: A Comprehensive Survey.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Multi-agent Reinforcement Learning: A Comprehensive Survey
Reference 30
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.282484Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 01685371-3625-47d6-a637-18bed9d705c0 · outbound
This paper cites Direct preference optimization: Your language model is secretly a reward model.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Direct preference optimization: Your language model is secretly a reward model
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.432658Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2c337282-0282-4e35-b81b-aebb6370eff7 · outbound
This paper cites OpenAI o1 System Card.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey OpenAI o1 System Card
Reference 32
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.266422Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 58e06a1a-2b09-4152-9ce7-7630c00b9215 · outbound
This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Reference 33
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.138145Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation dc1a6192-e18c-40a2-95a6-49ece5ccadf2 · outbound
This paper cites Openai o3 and o4-mini: Next-generation reasoning models.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Openai o3 and o4-mini: Next-generation reasoning models
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.405181Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4f5f303e-8ec3-4e6a-8cec-2d4640f9a9f7 · outbound
This paper cites A Comprehensive Survey of Reward Models: Taxonomy, Applications, Challenges, and Future.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey A Comprehensive Survey of Reward Models: Taxonomy, Applications, Challenges, and Future
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.183065Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ee604cd5-9a49-4432-86e8-bc5da3c09b6d · outbound
This paper cites A general theoretical paradigm to understand learning from human preferences.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey A general theoretical paradigm to understand learning from human preferences
Reference 36
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.402099Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8ec5c89e-c66c-46a1-86db-9b1020d8e098 · outbound
This paper cites Model alignment as prospect theoretic optimization.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Model alignment as prospect theoretic optimization
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.408414Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b2ab2c70-a02f-4218-9207-3bb352e10aca · outbound
This paper cites VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks
Reference 38
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.013620Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d47cb896-c4a9-49d3-91dc-6ff91af02719 · outbound
This paper cites Part i: Tricks or traps? a deep dive into rl for llm reasoning.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Part i: Tricks or traps? a deep dive into rl for llm reasoning
Reference 39
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.411470Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9ad6a137-df59-4412-8227-3f7838253bb7 · outbound
This paper cites Policy filtration for RLHF to mitigate noise in reward models.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Policy filtration for RLHF to mitigate noise in reward models
Reference 40
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.417568Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6179bf92-2916-48d4-8521-503ca9af2743 · outbound
This paper cites VinePPO: Refining Credit Assignment in RL Training of LLMs.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey VinePPO: Refining Credit Assignment in RL Training of LLMs
Reference 41
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-18T19:21:48.734746Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 518b9d2a-53a1-498b-8f60-db0e3e94ec91 · outbound
This paper cites Process supervision-guided policy optimization for code generation.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Process supervision-guided policy optimization for code generation
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.435823Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 85ca1492-1eb5-4891-b8f5-cfaa50b4e617 · outbound
This paper cites $\beta$-DPO: Direct preference optimization with dynamic $\beta$.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey $\beta$-DPO: Direct preference optimization with dynamic $\beta$
Reference 43
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.414636Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b69bf1a4-b249-410c-a560-13219291986a · outbound
This paper cites SimPO: Simple preference optimization with a reference- free reward.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey SimPO: Simple preference optimization with a reference- free reward
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.451664Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 79879293-fddf-4ffa-b97a-0261ab07e005 · outbound
This paper cites ORPO: Monolithic Preference Optimization without Reference Model.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey ORPO: Monolithic Preference Optimization without Reference Model
Reference 45
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.143700Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 808fbd4d-c3e0-4f1f-88bc-b8bff91c6cc2 · outbound
This paper cites Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Step-DPO: Step-wise Preference Optimization for Long-chain Reasoning of LLMs
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T23:58:29.262663Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9c6eb917-b493-4053-8f5d-207c5f29a10f · outbound
This paper cites Pruning Long Chain-of-Thought of Large Reasoning Models via Small-Scale Preference Optimization.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Pruning Long Chain-of-Thought of Large Reasoning Models via Small-Scale Preference Optimization
Reference 47
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.068374Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation dc87ac1d-53ef-498d-85f7-32e9f5e14888 · outbound
This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Reference 48
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.409093Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 63add13d-d4b5-4056-b866-47cd0302d06f · outbound
This paper cites Group Sequence Policy Optimization.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Group Sequence Policy Optimization
Reference 49
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.052038Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3a6d2884-cd12-4c1c-9b70-725a57238a5d · outbound
This paper cites Geometric-mean policy optimization.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Geometric-mean policy optimization
Reference 50
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.512545Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c5a2fb91-77c4-41df-a9a1-7264959a1673 · outbound
This paper cites ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey ProRL: Prolonged Reinforcement Learning Expands Reasoning Boundaries in Large Language Models
Reference 51
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T20:52:33.970587Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 122ae140-4eb5-4fc2-a6dc-cb60cc1aead6 · outbound
This paper cites ReCode: Reinforcing Code Generation with Reasoning-Process Rewards.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey ReCode: Reinforcing Code Generation with Reasoning-Process Rewards
Reference 52
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-18T19:21:48.003226Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 181db150-9ff2-45ac-a448-0f9a114bf0df · outbound
This paper cites Understanding R1-Zero-Like Training: A Critical Perspective.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Understanding R1-Zero-Like Training: A Critical Perspective
Reference 53
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.073138Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0a41b68b-c538-473c-99e2-959846fa58ca · outbound
This paper cites R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization
Reference 54
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.310900Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5ff6a99d-6525-439b-bee4-924540413cb4 · outbound
This paper cites SRPO: A Cross-Domain Implementation of Large-Scale Reinforcement Learning on LLM.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey SRPO: A Cross-Domain Implementation of Large-Scale Reinforcement Learning on LLM
Reference 55
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.803557Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e3703e59-508a-46ab-96f4-cc98e1583768 · outbound
This paper cites Bartoldson, Bhavya Kailkhura, Fan Lai, Jiawei Zhao, and Beidi Chen.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Bartoldson, Bhavya Kailkhura, Fan Lai, Jiawei Zhao, and Beidi Chen
Reference 56
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.395864Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b4d40336-1471-4269-b24f-77da40690d0f · outbound
This paper cites Act Only When It Pays: Efficient Reinforcement Learning for LLM Reasoning via Selective Rollouts.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Act Only When It Pays: Efficient Reinforcement Learning for LLM Reasoning via Selective Rollouts
Reference 57
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.638499Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4e4c5d38-576b-494f-b239-26b6df0b04bd · outbound
This paper cites RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning
Reference 58
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.689674Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 005cfd71-2387-45e5-adae-73e25cfbd840 · outbound
This paper cites GHPO: Adaptive Guidance for Stable and Efficient LLM Reinforcement Learning.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey GHPO: Adaptive Guidance for Stable and Efficient LLM Reinforcement Learning
Reference 59
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-18T19:21:48.567762Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b2df9d6a-be8e-4b2f-ba4f-e856480b8e1c · outbound
This paper cites Skywork R1V2: Multimodal Hybrid Reinforcement Learning for Reasoning.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Skywork R1V2: Multimodal Hybrid Reinforcement Learning for Reasoning
Reference 60
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.436079Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 81bbebef-4da3-4fce-b002-9c69f4ab4b61 · outbound
This paper cites Understanding Tool-Integrated Reasoning.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Understanding Tool-Integrated Reasoning
Reference 61
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.422826Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6e85e4c9-95eb-4636-b522-21e93dec0dec · outbound
This paper cites TreePO: Bridging the Gap of Policy Optimization and Efficacy and Inference Efficiency with Heuristic Tree-based Modeling.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey TreePO: Bridging the Gap of Policy Optimization and Efficacy and Inference Efficiency with Heuristic Tree-based Modeling
Reference 62
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.770589Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cf2cc2bc-117b-4cd6-847a-ba838efe361b · outbound
This paper cites EDGE-GRPO: Entropy-Driven GRPO with Guided Error Correction for Advantage Diversity.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey EDGE-GRPO: Entropy-Driven GRPO with Guided Error Correction for Advantage Diversity
Reference 63
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.764302Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 28aa91b4-ef3e-4a99-9638-7cb0a8cb5ec7 · outbound
This paper cites Depth-Breadth Synergy in RLVR: Unlocking LLM Reasoning Gains with Adaptive Exploration.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Depth-Breadth Synergy in RLVR: Unlocking LLM Reasoning Gains with Adaptive Exploration
Reference 64
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.758177Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d29ee98b-ad09-460f-b317-c504c15b29d7 · outbound
This paper cites arXiv preprint arXiv:2508.11408 , year=.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey arXiv preprint arXiv:2508.11408 , year=
Reference 65
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-18T19:21:48.441115Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e7d8987a-1e34-4486-b289-3db04d99566c · outbound
This paper cites Perception-Aware Policy Optimization for Multimodal Reasoning.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Perception-Aware Policy Optimization for Multimodal Reasoning
Reference 66
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.458569Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 22d80a05-e4f4-4ebe-913a-986afc61037c · outbound
This paper cites Pass@k training for adaptively balancing exploration and exploitation of large reasoning models.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Pass@k training for adaptively balancing exploration and exploitation of large reasoning models
Reference 67
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.385396Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 799af097-4862-4a75-989d-849b0b503152 · outbound
This paper cites Pass@k Training for Adaptively Balancing Exploration and Exploitation of Large Reasoning Models.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Pass@k Training for Adaptively Balancing Exploration and Exploitation of Large Reasoning Models
Reference 68
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.591192Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c150adfb-e10f-4dfa-9a3d-fbff1e0149e7 · outbound
This paper cites Llm-powered autonomous agents.lilianweng.github.io, Jun 2023.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Llm-powered autonomous agents.lilianweng.github.io, Jun 2023
Reference 69
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.399038Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3cb555e9-4f99-4d75-9994-d037a04b337d · outbound
This paper cites Agentsquare: Automatic LLM agent search in modular design space.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Agentsquare: Automatic LLM agent search in modular design space
Reference 70
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.381883Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation fddb92de-a7ef-4a3f-9b9a-e1b5541c8ca1 · outbound
This paper cites ISBN 979-8-89176-251-0.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey ISBN 979-8-89176-251-0
Reference 71
- Resolution
- metadata mismatch
- doi, observed 2026-05-18T19:21:46.625626Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a71b2933-cd04-489e-8ebe-cc12767fbab4 · outbound
This paper cites an unresolved cited work.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Unresolved cited work
Reference 72
- Resolution
- unresolved
- raw_fallback, observed 2026-05-18T19:22:50.388581Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 261db82e-e2be-4f29-8e14-7279eddd3777 · outbound
This paper cites LLM as a mastermind: A survey of strategic reasoning with large language models.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey LLM as a mastermind: A survey of strategic reasoning with large language models
Reference 73
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.366987Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 127adaf1-3e28-45c7-8f98-b287df11f931 · outbound
This paper cites Tool learning with foundation models.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Tool learning with foundation models
Reference 74
- Resolution
- verified exact
- doi, observed 2026-05-18T19:21:46.736820Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 69b943a9-d04f-449b-8703-96f8c92b8312 · outbound
This paper cites Elements of a theory of human problem solving.Psychological review, 65(3):151.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Elements of a theory of human problem solving.Psychological review, 65(3):151
Reference 75
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.363554Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation abbb2d01-8e70-491f-9ce1-4fc5e002bb0b · outbound
This paper cites Understanding the planning of LLM agents: A survey.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Understanding the planning of LLM agents: A survey
Reference 76
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.239818Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 66cab004-858c-4dc3-8d18-86affe20f3c6 · outbound
This paper cites Understanding the planning of LLM agents: A survey.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Understanding the planning of LLM agents: A survey
Reference 77
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:46.759838Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 42eeca06-3ad2-4c69-ba04-d4fd3d2760cc · outbound
This paper cites React: Synergizing reasoning and acting in language models.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey React: Synergizing reasoning and acting in language models
Reference 78
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.370819Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 42575813-c981-482d-9242-1614ec963728 · outbound
This paper cites Reasoning with language model is planning with world model.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Reasoning with language model is planning with world model
Reference 79
- Resolution
- malformed identifier
- raw_fallback, observed 2026-05-18T19:22:50.378508Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b9098cef-aa05-4468-ad87-3384385ee767 · outbound
This paper cites Language agent tree search unifies reasoning, acting, and planning in language models.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Language agent tree search unifies reasoning, acting, and planning in language models
Reference 80
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.351629Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ba991bd1-c692-43b5-b6ea-ba1d1a6dbab7 · outbound
This paper cites Planning without search: Refining frontier llms with offline goal-conditioned rl.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Planning without search: Refining frontier llms with offline goal-conditioned rl
Reference 81
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.111021Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a92bf813-e794-45f0-9ab9-3863594c978d · outbound
This paper cites Learning when to plan: Efficiently allocating test-time compute for llm agents.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Learning when to plan: Efficiently allocating test-time compute for llm agents
Reference 82
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.628450Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 71995afe-1318-4193-8be6-7f97b73df15b · outbound
This paper cites Deshmukh.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Deshmukh
Reference 83
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.160251Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ee4b2b14-200b-4ffe-979c-a74267c12c86 · outbound
This paper cites Trial and error: Exploration- based trajectory optimization of LLM agents.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Trial and error: Exploration- based trajectory optimization of LLM agents
Reference 84
- Resolution
- verified exact
- doi, observed 2026-05-18T19:21:46.667234Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1fe0a0f9-2855-47fc-98c1-e0c7a53c56ae · outbound
This paper cites Voyager: An open-ended embodied agent with large language models.Transactions on Machine Learning Research.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Voyager: An open-ended embodied agent with large language models.Transactions on Machine Learning Research
Reference 85
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.358704Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3f518fd1-643b-4a88-9340-2a1a77aafeae · outbound
This paper cites Dynamic speculative agent planning.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Dynamic speculative agent planning
Reference 86
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.708756Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4c2ea35a-3944-4662-935b-63a1c61f2ed2 · outbound
This paper cites Encouraging Good Processes Without the Need for Good Answers: Reinforcement Learning for LLM Agent Planning.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Encouraging Good Processes Without the Need for Good Answers: Reinforcement Learning for LLM Agent Planning
Reference 87
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.698956Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5e4d2d28-a510-4f85-b061-dcabb6b549b8 · outbound
This paper cites PilotRL: Training Language Model Agents via Global Planning-Guided Progressive Reinforcement Learning.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey PilotRL: Training Language Model Agents via Global Planning-Guided Progressive Reinforcement Learning
Reference 88
- Resolution
- verified exact
- arxiv_id, observed 2026-07-29T02:24:11.040454Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 68e79a83-d91e-47bf-8ebe-3ea74e9f02cf · outbound
This paper cites Planner-r1: Reward shaping enables efficient agentic rl with smaller llms.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Planner-r1: Reward shaping enables efficient agentic rl with smaller llms
Reference 89
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.374625Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d2762523-ea31-441f-93f4-1145ba12a75d · outbound
This paper cites Planner-r1: Reward shaping enables efficient agentic rl with smaller llms.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Planner-r1: Reward shaping enables efficient agentic rl with smaller llms
Reference 90
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.703490Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 63e3f720-3a8b-4398-ba5c-98ae87fe806d · outbound
This paper cites A brain-inspired agentic architec- ture to improve planning with llms.Nature Communications, 16(1):8633.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey A brain-inspired agentic architec- ture to improve planning with llms.Nature Communications, 16(1):8633
Reference 91
- Resolution
- verified exact
- doi, observed 2026-05-18T19:21:46.680300Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 08887fbe-0b1f-413f-9d99-f07452820a75 · outbound
This paper cites Toolformer: Language models can teach them- selves to use tools.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Toolformer: Language models can teach them- selves to use tools
Reference 92
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.348198Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7d149853-178e-4757-a71c-fdf5f94f7ea8 · outbound
This paper cites FireAct: Toward Language Agent Fine-tuning.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey FireAct: Toward Language Agent Fine-tuning
Reference 93
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T19:21:48.752794Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 30507396-f3d7-4e55-9e8e-68627b5ccdd0 · outbound
This paper cites Knowledge-Centric Hallucination Detection.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Knowledge-Centric Hallucination Detection
Reference 94
- Resolution
- metadata mismatch
- doi, observed 2026-05-18T19:21:46.686021Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d5de3d6c-f9bf-4fc6-be28-3eff2b34e99f · outbound
This paper cites Agent-FLAN: Designing data and methods of effective agent tuning for large language models.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Agent-FLAN: Designing data and methods of effective agent tuning for large language models
Reference 95
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.343624Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 035db9a4-bf6e-4035-89f2-2e35b5aca205 · outbound
This paper cites doi: 10.18653/v1/2024.findings-acl.557.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey doi: 10.18653/v1/2024.findings-acl.557
Reference 96
- Resolution
- verified exact
- doi, observed 2026-05-18T19:21:46.641108Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ae81e564-ef8e-4cbc-9baa-ae7934baf2ff · outbound
This paper cites Agentbank: Towards generalized llm agents via fine-tuning on 50000+ interaction trajectories.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Agentbank: Towards generalized llm agents via fine-tuning on 50000+ interaction trajectories
Reference 97
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.354885Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9893c56f-167f-4db3-88cd-898bf89c4dfd · outbound
This paper cites API-Bank : A comprehensive benchmark for tool-augmented LLMs.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey API-Bank : A comprehensive benchmark for tool-augmented LLMs
Reference 98
- Resolution
- verified exact
- doi, observed 2026-05-18T19:21:46.696153Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 97d5aa68-d662-47c0-b740-2d8553e714df · outbound
This paper cites ToolRL: Reward is All Tool Learning Needs.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey ToolRL: Reward is All Tool Learning Needs
Reference 99
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T19:21:48.675756Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d4db3474-c124-4d39-aa05-13d3579a4cd9 · outbound
This paper cites Acting less is reasoning more! teaching model to act efficiently.
The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Acting less is reasoning more! teaching model to act efficiently
Reference 100
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-18T19:22:50.392161Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Pith citing papers
Observation d0843f26-55b0-4b87-80d1-6ab94b23f010 · inbound
What Factors Affect LLMs and RLLMs in Financial Question Answering? cites this paper.
What Factors Affect LLMs and RLLMs in Financial Question Answering? The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 22
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-19T05:07:04.507042Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c2a11b12-6c43-47a2-a4f2-f527bcfd31f6 · inbound
HiPRAG: Hierarchical Process Rewards for Efficient Agentic Retrieval Augmented Generation cites this paper.
HiPRAG: Hierarchical Process Rewards for Efficient Agentic Retrieval Augmented Generation The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 29
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-18T09:31:11.965415Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8bdd12ed-b601-491c-adce-b6b0c8e02f79 · inbound
Graph-Enhanced Policy Optimization in LLM Agent Training cites this paper.
Graph-Enhanced Policy Optimization in LLM Agent Training The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T07:17:44.680792Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 23833c0c-2daa-4777-bb4e-3bbb44933c9d · inbound
Agentic Learner with Grow-and-Refine Multimodal Semantic Memory cites this paper.
Agentic Learner with Grow-and-Refine Multimodal Semantic Memory The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 46
- Resolution
- verified exact
- local_arxiv, observed 2026-05-17T04:29:01.636424Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 92811bb6-2bb7-4dc7-a1f5-a1d8d3323824 · inbound
Training Multi-Image Vision Agents via End2End Reinforcement Learning cites this paper.
Training Multi-Image Vision Agents via End2End Reinforcement Learning The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 60
- Resolution
- verified exact
- local_arxiv, observed 2026-05-17T01:01:24.314958Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c1ee493e-32f3-4ecb-b41d-38c9b4c1c565 · inbound
Agentic Reasoning for Large Language Models cites this paper.
Agentic Reasoning for Large Language Models The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 56
- Resolution
- verified exact
- local_arxiv, observed 2026-05-17T15:14:25.827351Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation beb3b442-90aa-4ef1-9b55-b1494c07e1e6 · inbound
S$^2$GR: Stepwise Semantic-Guided Reasoning in Latent Space for Generative Recommendation cites this paper.
S$^2$GR: Stepwise Semantic-Guided Reasoning in Latent Space for Generative Recommendation The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 42
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T14:24:12.918784Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d1b03946-a403-41ed-a954-c463b59934b3 · inbound
EcoGym: Evaluating LLMs for Long-Horizon Plan-and-Execute in Interactive Economies cites this paper.
EcoGym: Evaluating LLMs for Long-Horizon Plan-and-Execute in Interactive Economies The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 41
- Resolution
- verified exact
- local_arxiv, observed 2026-05-16T05:57:24.560026Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a3a7ae48-876a-4096-9503-ade0391bc9f1 · inbound
SciAgentGym: Benchmarking Multi-Step Scientific Tool-use in LLM Agents cites this paper.
SciAgentGym: Benchmarking Multi-Step Scientific Tool-use in LLM Agents The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T23:41:45.930272Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation adcc7487-9bed-42e4-b1cd-e7fca77e05a9 · inbound
AgentCE-Bench: Agent Configurable Evaluation with Scalable Horizons and Controllable Difficulty under Lightweight Environments cites this paper.
AgentCE-Bench: Agent Configurable Evaluation with Scalable Horizons and Controllable Difficulty under Lightweight Environments The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 24
- Resolution
- verified exact
- local_arxiv, observed 2026-05-10T23:30:49.538465Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8edec5fe-a6ba-4813-ad89-71f80131a018 · inbound
Towards Knowledgeable Deep Research: Framework and Benchmark cites this paper.
Towards Knowledgeable Deep Research: Framework and Benchmark The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 43
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T05:10:54.620416Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0fdc4e7b-aceb-41ba-a193-4fd9624d5aea · inbound
StaRPO: Stability-Augmented Reinforcement Policy Optimization cites this paper.
StaRPO: Stability-Augmented Reinforcement Policy Optimization The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 42
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T05:21:00.050350Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4a6fd09a-7f0f-4c66-888e-bfd364676651 · inbound
E3-TIR: Enhanced Experience Exploitation for Tool-Integrated Reasoning cites this paper.
E3-TIR: Enhanced Experience Exploitation for Tool-Integrated Reasoning The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 36
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T05:25:59.858348Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e20370d8-dd87-4dfd-a222-7e82f415063a · inbound
From Reasoning to Agentic: Credit Assignment in Reinforcement Learning for Large Language Models cites this paper.
From Reasoning to Agentic: Credit Assignment in Reinforcement Learning for Large Language Models The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 36
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T07:30:58.534608Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c0add783-059e-4a77-b22d-44111e535a31 · inbound
AIT Academy: Cultivating the Complete Agent with a Confucian Three-Domain Curriculum cites this paper.
AIT Academy: Cultivating the Complete Agent with a Confucian Three-Domain Curriculum The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 18
- Resolution
- verified exact
- local_arxiv, observed 2026-05-10T09:43:49.907062Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2e0677ef-c984-4342-91ac-3cc70a947423 · inbound
Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures cites this paper.
Multi-Agent Systems: From Classical Paradigms to Large Foundation Model-Enabled Futures The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 22
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T11:51:03.843942Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1a0a8b86-ff0b-471a-bd3b-9e16118db1ff · inbound
Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence cites this paper.
Agent-World: Scaling Real-World Environment Synthesis for Evolving General Agent Intelligence The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 130
- Resolution
- verified exact
- local_arxiv, observed 2026-05-10T05:25:54.680633Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 307ac012-d529-4d07-9023-23f6f40fd6f5 · inbound
StepPO: Step-Aligned Policy Optimization for Agentic Reinforcement Learning cites this paper.
StepPO: Step-Aligned Policy Optimization for Agentic Reinforcement Learning The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 38
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T11:56:29.963355Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6001819a-e57f-4286-a0be-10e7bb80ca33 · inbound
StepPO: Step-Aligned Policy Optimization for Agentic Reinforcement Learning cites this paper.
StepPO: Step-Aligned Policy Optimization for Agentic Reinforcement Learning The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 41
- Resolution
- verified exact
- local_arxiv, observed 2026-07-05T12:30:59.985134Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 29c2dcb9-8346-4ef4-accb-b9041e761ea6 · inbound
SceneOrchestra: Efficient Agentic 3D Scene Synthesis via Full Tool-Call Trajectory Generation cites this paper.
SceneOrchestra: Efficient Agentic 3D Scene Synthesis via Full Tool-Call Trajectory Generation The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 42
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T12:31:06.624691Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ad6aa5a1-a4cd-48c8-9a86-ba8445237e5e · inbound
Rethinking Agentic Reinforcement Learning In Large Language Models cites this paper.
Rethinking Agentic Reinforcement Learning In Large Language Models The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 123
- Resolution
- verified exact
- local_arxiv, observed 2026-05-12T10:21:29.931588Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6c2b1663-d5d3-46db-ac4d-2db269f4bc6b · inbound
Rethinking Agentic Reinforcement Learning In Large Language Models cites this paper.
Rethinking Agentic Reinforcement Learning In Large Language Models The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 123
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T22:11:17.477480Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9000084b-0722-4fd9-a29f-22b7c57b3e1e · inbound
Rethinking Agentic Reinforcement Learning In Large Language Models cites this paper.
Rethinking Agentic Reinforcement Learning In Large Language Models The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 123
- Resolution
- verified exact
- local_arxiv, observed 2026-05-19T17:02:40.867075Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c0cece03-ef9f-4792-972c-2e16d5fd7362 · inbound
Learning How and What to Memorize: Cognition-Inspired Two-Stage Optimization for Evolving Memory cites this paper.
Learning How and What to Memorize: Cognition-Inspired Two-Stage Optimization for Evolving Memory The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 178
- Resolution
- verified exact
- local_arxiv, observed 2026-05-11T15:51:34.365503Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e92c6fc1-7400-4258-afee-285011440b5e · inbound
Generate, Filter, Control, Replay: A Comprehensive Survey of Rollout Strategies for LLM Reinforcement Learning cites this paper.
Generate, Filter, Control, Replay: A Comprehensive Survey of Rollout Strategies for LLM Reinforcement Learning The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 165
- Resolution
- verified exact
- local_arxiv, observed 2026-05-10T23:15:49.622476Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f0194b7a-1933-48bb-86ef-b2fecd5e8553 · inbound
Skill1: Unified Evolution of Skill-Augmented Agents via Reinforcement Learning cites this paper.
Skill1: Unified Evolution of Skill-Augmented Agents via Reinforcement Learning The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 72
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-11T20:01:12.713998Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 32f7ce1b-c029-47aa-bd4a-5b64f5302d08 · inbound
Skill1: Unified Evolution of Skill-Augmented Agents via Reinforcement Learning cites this paper.
Skill1: Unified Evolution of Skill-Augmented Agents via Reinforcement Learning The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 72
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-11T04:00:56.870208Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8917f524-9daa-4a54-8631-31c83540d360 · inbound
Skill1: Unified Evolution of Skill-Augmented Agents via Reinforcement Learning cites this paper.
Skill1: Unified Evolution of Skill-Augmented Agents via Reinforcement Learning The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 72
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-13T07:17:28.188774Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6705439e-9314-460b-ae08-4e24b5a2f304 · inbound
StraTA: Incentivizing Agentic Reinforcement Learning with Strategic Trajectory Abstraction cites this paper.
StraTA: Incentivizing Agentic Reinforcement Learning with Strategic Trajectory Abstraction The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 3
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-11T20:11:12.262776Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6411ce64-b1ed-4acf-a284-d52677013cc2 · inbound
Personalizing LLMs with Binary Feedback: A Preference-Corrected Optimization Framework cites this paper.
Personalizing LLMs with Binary Feedback: A Preference-Corrected Optimization Framework The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 39
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-12T02:41:17.572918Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ff787be5-ad14-4556-bcbd-6f07b151209e · inbound
Learning Agentic Policy from Action Guidance cites this paper.
Learning Agentic Policy from Action Guidance The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 78
- Resolution
- verified exact
- local_arxiv, observed 2026-05-13T05:07:17.608879Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 592ecb5c-3926-42e0-9019-97984e70e84f · inbound
Reinforced Collaboration in Multi-Agent Flow Networks cites this paper.
Reinforced Collaboration in Multi-Agent Flow Networks The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 60
- Resolution
- verified exact
- local_arxiv, observed 2026-05-14T20:42:57.113425Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1c3ca816-0b82-4621-8982-83c43c5c1428 · inbound
NEWTON: Agentic Planning for Physically Grounded Video Generation cites this paper.
NEWTON: Agentic Planning for Physically Grounded Video Generation The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 41
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T10:58:13.729421Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e6690489-b4a0-4ba0-a2f6-f1c670648b1f · inbound
Trustworthy Agent Network: Trust in Agent Networks Must Be Baked In, Not Bolted On cites this paper.
Trustworthy Agent Network: Trust in Agent Networks Must Be Baked In, Not Bolted On The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 71
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T10:33:12.352568Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 279c5188-7d12-4d1c-8ec6-32364f4b2214 · inbound
Echo: Learning from Experience Data via User-Driven Refinement cites this paper.
Echo: Learning from Experience Data via User-Driven Refinement The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 22
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T06:41:10.745267Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5a28c917-b334-4e04-b1b9-1c306c65e98e · inbound
Learning to Act under Noise: Enhancing Agent Robustness via Noisy Environments cites this paper.
Learning to Act under Noise: Enhancing Agent Robustness via Noisy Environments The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 27
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T16:53:40.551897Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation bca960fa-fcc1-4ee5-9170-aad48d307215 · inbound
Mags-RL: Wearing Multimodal LLMs a Magnifying Glass via Agentic Reinforcement Learning For Complex Scene Reasoning cites this paper.
Mags-RL: Wearing Multimodal LLMs a Magnifying Glass via Agentic Reinforcement Learning For Complex Scene Reasoning The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 49
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-06-29T13:43:28.975560Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c9994a9a-d795-4eca-88b9-8282b8dc8293 · inbound
Libra: Efficient Resource Management for Agentic RL Post-Training cites this paper.
Libra: Efficient Resource Management for Agentic RL Post-Training The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 62
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T02:16:27.165537Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a486bd6a-57e1-454c-b174-7cc35e28dbef · inbound
EvoDS: Self-Evolving Autonomous Data Science Agent with Skill Learning and Context Management cites this paper.
EvoDS: Self-Evolving Autonomous Data Science Agent with Skill Learning and Context Management The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 75
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T03:56:35.113117Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f5b1c40d-9b05-4f54-b95d-ebeb54d0a35e · inbound
Co-Evolving Skill Generation and Policy Optimization cites this paper.
Co-Evolving Skill Generation and Policy Optimization The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T22:47:26.427426Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ad6b1f5b-7f82-42e4-b3b8-027497a35524 · inbound
Claw-R1: A Step-Level Data Middleware System for Agentic Reinforcement Learning cites this paper.
Claw-R1: A Step-Level Data Middleware System for Agentic Reinforcement Learning The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 29
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T00:07:28.226428Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ffe115d7-9925-48de-b56e-50e4915e100e · inbound
APPO: Agentic Procedural Policy Optimization cites this paper.
APPO: Agentic Procedural Policy Optimization The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 94
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T09:37:49.371227Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8e5d4caa-6992-4673-bb21-e69135855cd3 · inbound
APPO: Agentic Procedural Policy Optimization cites this paper.
APPO: Agentic Procedural Policy Optimization The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 94
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T02:12:35.232674Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0cd33109-5bc7-416d-907d-560d5cd9e59c · inbound
PDAGENT-BENCH: Characterizing, Grounding, and Architecting LLM Agents for VLSI Physical Design cites this paper.
PDAGENT-BENCH: Characterizing, Grounding, and Architecting LLM Agents for VLSI Physical Design The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 36
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T19:08:49.836672Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation eb877cd0-e9f2-47e4-85a9-9a7e727956d7 · inbound
Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning cites this paper.
Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 260
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T08:09:40.470466Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 13eb0052-5713-4b22-84b9-572d6b235405 · inbound
AIR: Adaptive Interleaved Reasoning with Code in MLLMs cites this paper.
AIR: Adaptive Interleaved Reasoning with Code in MLLMs The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 11
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-04T10:09:45.005873Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 94344ad7-f12f-49de-9845-958e838cddb3 · inbound
OPID: On-Policy Skill Distillation for Agentic Reinforcement Learning cites this paper.
OPID: On-Policy Skill Distillation for Agentic Reinforcement Learning The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 9
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-04T13:29:52.131453Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cc852ecd-9b9d-426e-bbbb-4bc1701b7652 · inbound
Empowering GUI Agents via Autonomous Experience Exploration and Hindsight Experience Utilization for Task Planning cites this paper.
Empowering GUI Agents via Autonomous Experience Exploration and Hindsight Experience Utilization for Task Planning The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 20
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-04T14:29:53.373940Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9879578b-5bcb-4dc6-ae8e-5dfd175261ba · inbound
Stop Hand-Holding Your Coding Agent: Engineering the Loops that Replace Step-by-Step Prompting cites this paper.
Stop Hand-Holding Your Coding Agent: Engineering the Loops that Replace Step-by-Step Prompting The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 56
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T20:47:22.214005Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 33657ff9-1549-4848-9780-49c8acfa3dd4 · inbound
Next-Generation Agentic Reinforcement Learning Systems Enable Self-Evolving Agents cites this paper.
Next-Generation Agentic Reinforcement Learning Systems Enable Self-Evolving Agents The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T06:06:40.599975Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 76af6b6d-0be3-4282-b302-959eb43ce550 · inbound
Next-Generation Agentic Reinforcement Learning Systems Enable Self-Evolving Agents cites this paper.
Next-Generation Agentic Reinforcement Learning Systems Enable Self-Evolving Agents The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-07-03T18:48:49.516258Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 59fbeac2-527b-467f-85be-ae71a3a1a923 · inbound
Information Gain-based Rollout Policy Optimization: An Adaptive Tree-Structured Rollout Approach for Multi-Turn LLM Agents cites this paper.
Information Gain-based Rollout Policy Optimization: An Adaptive Tree-Structured Rollout Approach for Multi-Turn LLM Agents The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 6
- Resolution
- verified exact
- local_arxiv, observed 2026-07-08T13:04:56.742129Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3840bc46-ce83-427a-8711-a6671b20ec41 · inbound
Mathematical methods of reinforcement learning cites this paper.
Mathematical methods of reinforcement learning The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-07-09T22:56:37.774476Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation fd6df471-3b24-4d47-9423-2a9a6012f5b4 · inbound
Entropy Pacing Policy Optimization for Multi-Task Agentic Reinforcement Learning cites this paper.
Entropy Pacing Policy Optimization for Multi-Task Agentic Reinforcement Learning The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 29
- Resolution
- verified exact
- local_arxiv, observed 2026-07-09T18:26:26.279667Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ddc527bd-8339-4e66-ade0-586f28941835 · inbound
The Path to Self-Evolving Clinical Systems: Scaling Medical Agents from Assistance to Autonomy cites this paper.
The Path to Self-Evolving Clinical Systems: Scaling Medical Agents from Assistance to Autonomy The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 300
- Resolution
- unresolved
- no resolver link, observed 2026-07-14T06:30:16.612345Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ac28d4f5-fac1-44ee-887f-b466e24e46be · inbound
Multi-Agent Collaborative Reasoning with Tool-Augmented Evidence for Urban Region Profiling cites this paper.
Multi-Agent Collaborative Reasoning with Tool-Augmented Evidence for Urban Region Profiling The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 59
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T04:54:14.134572Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 93df52ba-fc98-4581-b12a-702612842bfc · inbound
ToolAnchor: Anchoring Counterfactual Context to Boost Agentic Tool-use Capability cites this paper.
ToolAnchor: Anchoring Counterfactual Context to Boost Agentic Tool-use Capability The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T06:36:47.629823Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fdcfbaf5-e0f4-40e0-ac83-ece8e809376b · inbound
Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RL cites this paper.
Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RL The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 119
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T14:50:18.593672Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6477b146-22e0-4b29-84b7-91020de15fca · inbound
From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training cites this paper.
From Outcomes to Actions: Leveraging Hindsight for Long-Horizon Language Agent Training The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 21
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T09:45:49.621635Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 64f52e8b-3915-41ba-a444-7e1ec7a8b90b · inbound
AgentOmnia: Scaling Agentic Models for Full-Scenario Applications cites this paper.
AgentOmnia: Scaling Agentic Models for Full-Scenario Applications The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 108
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T03:38:25.752951Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4478aa35-c581-4ddd-9bf5-6208b2bf3672 · inbound
OmniQEC: discovering practical quantum error-correcting codes by an AI scientist cites this paper.
OmniQEC: discovering practical quantum error-correcting codes by an AI scientist The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 85
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T01:20:49.101238Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7a145b9c-9181-430b-acfa-2b13de815d79 · inbound
SkillRise: Agentic Reinforcement Learning for Cross-Task Skill Evolution cites this paper.
SkillRise: Agentic Reinforcement Learning for Cross-Task Skill Evolution The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-07-30T21:12:59.446937Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 48e765bb-755c-4a4d-b144-67fca8c8c5da · inbound
Deep Reinforcement Learning: From First Principles to Reasoning Models cites this paper.
Deep Reinforcement Learning: From First Principles to Reasoning Models The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T01:16:05.118218Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 27ca895f-cc55-44a1-8c62-003964f5102b · inbound
From Simple QA to Deep Research: A Verifiable Benchmark Constructed through Iterative Task Evolution cites this paper.
From Simple QA to Deep Research: A Verifiable Benchmark Constructed through Iterative Task Evolution The Landscape of Agentic Reinforcement Learning for LLMs: A Survey
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T13:31:24.753889Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.