Paper Citation Record · LEDGER

ZeroSearch: Incentivize the Search Capability of LLMs without Searching

As of 7 August 2026, this Paper Citation Record lists 49 of 49 outbound references and 62 inbound Pith citation observations for arXiv:2505.04588.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2505.04588 v3

Coverage vector

measured 49 of 49 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-22T16:05:04.715678Z

measured 111 of 111 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 62 of 62 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:37:29.355209Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

49 of 49 outbound references displayed

verified exact38
verified fuzzy7
unresolved4
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 0ed22e2a-7a87-4995-a4d4-fb087f4355d0 · outbound

This paper cites an unresolved cited work.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Unresolved cited work

Reference 1

Resolution: unresolved; raw_fallback, observed 2026-05-22T16:06:46.521909Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b3e0558a-fb04-49e5-b3dc-0261cad3e012 · outbound

This paper cites Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Attributed Question Answering: Evaluation and Modeling for Attributed Large Language Models

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:06:46.008263Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fc1a83de-39c9-4bd2-8f66-1bb346121f33 · outbound

This paper cites PaLM: Scaling Language Modeling with Pathways.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching PaLM: Scaling Language Modeling with Pathways

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-22T16:06:46.002126Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e2108120-e918-49c2-aef3-21bdf03a2d61 · outbound

This paper cites The Llama 3 Herd of Models.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching The Llama 3 Herd of Models

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-05-22T16:06:45.945313Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation daf9d241-e315-4d5f-a07d-5be4ab74a255 · outbound

This paper cites AirRAG: Autonomous Strategic Planning and Reasoning Steer Retrieval Augmented Generation.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching AirRAG: Autonomous Strategic Planning and Reasoning Steer Retrieval Augmented Generation

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:06:45.871947Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 118043ca-bc29-4d0d-a07e-4ca7552b19c4 · outbound

This paper cites RARR: Researching and Revising What Language Models Say, Using Language Models.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching RARR: Researching and Revising What Language Models Say, Using Language Models

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:06:46.036250Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 04cfbf3d-48cb-4c16-bd2a-32fcc5b7d7ef · outbound

This paper cites Self-Adaptive Gamma Context-Aware SSM-based Model for Metal Defect Detection.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Self-Adaptive Gamma Context-Aware SSM-based Model for Metal Defect Detection

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:06:45.917347Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d28a5430-c1ac-4c5e-8573-a16d1fc5e446 · outbound

This paper cites Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Constructing A Multi-hop QA Dataset for Comprehensive Evaluation of Reasoning Steps

Reference 8

Resolution: verified exact; local_arxiv, observed 2026-05-22T16:06:45.837584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 94780eef-91aa-44b3-9c9f-18006e33b353 · outbound

This paper cites Hou and et al.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Hou and et al

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:06:46.503858Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ecbde63c-b3e4-46bb-87ea-b473e8a1299c · outbound

This paper cites MathPrompter: Mathematical Reasoning using Large Language Models.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching MathPrompter: Mathematical Reasoning using Large Language Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:06:45.894985Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 88b13138-7e8c-4c15-aa85-363ba0b44bc7 · outbound

This paper cites Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Adaptive-RAG: Learning to Adapt Retrieval-Augmented Large Language Models through Question Complexity

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:06:45.991331Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b4e8efe0-8fd3-447e-9416-bcbe900edc2c · outbound

This paper cites an unresolved cited work.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-05-22T16:06:46.506971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 57606a0f-5ce6-4c1e-86f4-69a5ca8748fd · outbound

This paper cites RAG-Star: Enhancing Deliberative Reasoning with Retrieval Augmented Verification and Refinement.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching RAG-Star: Enhancing Deliberative Reasoning with Retrieval Augmented Verification and Refinement

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:06:45.889296Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 56fe818b-eff3-4366-8fa8-a5ab4045d2de · outbound

This paper cites Enhancing LLM Reasoning with Reward-guided Tree Search.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Enhancing LLM Reasoning with Reward-guided Tree Search

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:06:45.978606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9e4f8f68-2215-44a9-820e-2c06d14a9293 · outbound

This paper cites Jiang, F.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Jiang, F

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:06:46.517680Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 15cb8905-537b-4941-9cde-da4944e50433 · outbound

This paper cites Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-05-22T16:06:45.857185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation eae25a6b-4832-4ec9-8cac-4022f3f16cf1 · outbound

This paper cites TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching TriviaQA: A Large Scale Distantly Supervised Challenge Dataset for Reading Comprehension

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-05-22T16:06:45.902609Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a4edba05-8aa9-4ca2-a615-ef8a9a364480 · outbound

This paper cites Kumar and et al.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Kumar and et al

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:06:46.513766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7fa83612-8d22-4847-b208-117bf14f8551 · outbound

This paper cites The cat-bat map, the figure-eight knot, and the five orbifolds.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching The cat-bat map, the figure-eight knot, and the five orbifolds

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:06:45.964714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 53b9393f-0f96-4731-8160-a612152f4c5d · outbound

This paper cites Kwiatkowski, J.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Kwiatkowski, J

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:06:46.510097Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e9e61894-91b2-49ae-abb0-9c96ee73283d · outbound

This paper cites Lewkowycz, A.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Lewkowycz, A

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:06:46.541283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a37fc1d9-9785-4e78-bdd4-d47b1624ac4e · outbound

This paper cites Search-o1: Agentic Search-Enhanced Large Reasoning Models.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Search-o1: Agentic Search-Enhanced Large Reasoning Models

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-05-22T16:06:45.851145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d3546a73-0bf7-43d3-a7fc-fc2f07d15451 · outbound

This paper cites WebThinker: Empowering Large Reasoning Models with Deep Research Capability.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching WebThinker: Empowering Large Reasoning Models with Deep Research Capability

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-05-22T16:06:46.046975Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6e915c3f-8ba6-4759-8de3-a8b8b166596a · outbound

This paper cites RetroLLM: Empowering Large Language Models to Retrieve Fine-grained Evidence within Generation.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching RetroLLM: Empowering Large Language Models to Retrieve Fine-grained Evidence within Generation

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:06:46.052602Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 20a49fdd-6099-4342-b3cb-84ab51406479 · outbound

This paper cites Can We Further Elicit Reasoning in LLMs? Critic-Guided Planning with Retrieval-Augmentation for Solving Challenging Tasks.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Can We Further Elicit Reasoning in LLMs? Critic-Guided Planning with Retrieval-Augmentation for Solving Challenging Tasks

Reference 25

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:06:45.909112Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c8eaccbd-2f49-46a3-af06-b3db74d8f948 · outbound

This paper cites When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching When Not to Trust Language Models: Investigating Effectiveness of Parametric and Non-Parametric Memories

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-05-22T16:06:45.865737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2e352b9b-a5b6-4e86-aefb-a608fa625ace · outbound

This paper cites Teaching language models to support answers with verified quotes.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Teaching language models to support answers with verified quotes

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-05-22T16:06:45.929246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 40350ada-7b3d-46af-a72d-22cc6446deb2 · outbound

This paper cites Measuring and Narrowing the Compositionality Gap in Language Models.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Measuring and Narrowing the Compositionality Gap in Language Models

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-05-22T16:06:45.923648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 08b0c24c-afe1-4f95-a02b-137390c3baa6 · outbound

This paper cites In-Context Retrieval-Augmented Language Models.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching In-Context Retrieval-Augmented Language Models

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:06:45.985020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 031031ae-629b-47f3-a859-97cae4a60cf7 · outbound

This paper cites Measuring Attribution in Natural Language Generation Models.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Measuring Attribution in Natural Language Generation Models

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:06:46.041523Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 67d26f8d-49dd-41e0-b1ca-ea516ada956a · outbound

This paper cites Proximal Policy Optimization Algorithms.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Proximal Policy Optimization Algorithms

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-05-22T16:06:46.058115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cdfa4567-832d-444a-8a0a-19f19251f6e4 · outbound

This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-05-22T16:06:45.877971Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f77cde22-834b-4989-82f7-0570fd407320 · outbound

This paper cites REPLUG: Retrieval-Augmented Black-Box Language Models.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching REPLUG: Retrieval-Augmented Black-Box Language Models

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-05-22T16:06:45.844247Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a6d116cf-06fb-4e49-9dd9-3f466ff9884e · outbound

This paper cites Retrieval Augmentation Reduces Hallucination in Conversation.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Retrieval Augmentation Reduces Hallucination in Conversation

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:06:45.935574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cce7010b-dbf3-4d25-9c26-4f2f1c6cfba9 · outbound

This paper cites R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-05-22T16:06:45.950993Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 8e92d8c3-fda0-49f0-881d-f15b7b83b2d5 · outbound

This paper cites Galactica: A Large Language Model for Science.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Galactica: A Large Language Model for Science

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-05-22T16:06:46.025191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cf064b4b-ada2-4e87-a7da-aef48871542a · outbound

This paper cites Trivedi, N.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Trivedi, N

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:06:46.533639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 406c6ac2-20fe-4deb-8845-57cb4bc38221 · outbound

This paper cites an unresolved cited work.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Unresolved cited work

Reference 38

Resolution: unresolved; raw_fallback, observed 2026-05-22T16:06:46.537542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation f9335210-c8ab-4c38-b471-6f8617752a2e · outbound

This paper cites Evaluating Mathematical Reasoning Beyond Accuracy.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Evaluating Mathematical Reasoning Beyond Accuracy

Reference 39

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:06:46.064052Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c3b72591-3104-4a65-8a49-7f1ac7114e0c · outbound

This paper cites LPML: LLM-Prompting Markup Language for Mathematical Reasoning.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching LPML: LLM-Prompting Markup Language for Mathematical Reasoning

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:06:45.959021Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation fb050e05-cf9e-4512-a379-497430c95abd · outbound

This paper cites Qwen2.5 Technical Report.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Qwen2.5 Technical Report

Reference 41

Resolution: verified exact; local_arxiv, observed 2026-05-22T16:06:46.030639Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a0afbbf9-3877-4281-8ae6-07cbde7ce82e · outbound

This paper cites HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching HotpotQA: A Dataset for Diverse, Explainable Multi-hop Question Answering

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-05-22T16:06:46.069057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 45e4c17c-8699-4064-8669-a27db9fb026b · outbound

This paper cites Answering Questions by Meta-Reasoning over Multiple Chains of Thought.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Answering Questions by Meta-Reasoning over Multiple Chains of Thought

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:06:45.883756Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e4a03570-0332-4bb7-b95e-65484bc90b04 · outbound

This paper cites Generate rather than Retrieve: Large Language Models are Strong Context Generators.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Generate rather than Retrieve: Large Language Models are Strong Context Generators

Reference 44

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:06:46.013992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 536128ef-2c81-465e-bf0a-356fbd207ff3 · outbound

This paper cites Zhang, Z.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Zhang, Z

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-05-22T16:06:46.525795Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 802f165d-b378-4788-a62f-47876286c3c1 · outbound

This paper cites A Survey of Large Language Models.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching A Survey of Large Language Models

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-05-22T16:06:45.971752Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ad3c94f8-a89d-43c3-b91c-98cd25a3ee7b · outbound

This paper cites Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Marco-o1: Towards Open Reasoning Models for Open-Ended Solutions

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-22T16:06:46.019822Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 423d9367-d1ce-40c2-bd0c-21b5335575bf · outbound

This paper cites DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments

Reference 48

Resolution: verified exact; local_arxiv, observed 2026-05-22T16:06:45.996945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d6438004-c379-44e4-9fb9-64d3d0642d2a · outbound

This paper cites an unresolved cited work.

ZeroSearch: Incentivize the Search Capability of LLMs without Searching Unresolved cited work

Reference 49

Resolution: unresolved; raw_fallback, observed 2026-05-22T16:06:46.529694Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Pith citing papers

Observation 766e418f-a43a-43e2-a5ab-47b01d31dc54 · inbound

Group-in-Group Policy Optimization for LLM Agent Training cites this paper.

Group-in-Group Policy Optimization for LLM Agent Training ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-17T17:44:13.577137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 79501cbb-1579-41cb-a840-1559fde82470 · inbound

Advancing Multi-Agent RAG Systems with Minimalist Reinforcement Learning cites this paper.

Advancing Multi-Agent RAG Systems with Minimalist Reinforcement Learning ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 71

Resolution: verified exact; local_arxiv, observed 2026-05-22T13:34:53.194692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 93347886-c143-41e3-9983-72c4266c1ae7 · inbound

Coordinating Search-Informed Reasoning and Reasoning-Guided Search in Claim Verification cites this paper.

Coordinating Search-Informed Reasoning and Reasoning-Guided Search in Claim Verification ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T05:37:29.355209Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c6895831-5c05-4759-82e2-952c8ab45ca1 · inbound

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models cites this paper.

Reinforcement Fine-Tuning for Reasoning towards Multi-Step Multi-Source Search in Large Language Models ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T05:20:04.635328Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 10349242-37f1-4f2e-b007-f0b20d7ab42a · inbound

L0: Reinforcement Learning to Become General Agents cites this paper.

L0: Reinforcement Learning to Become General Agents ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-06T21:45:00.471283Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 36f5341b-84e6-4057-8771-d0dde25fb063 · inbound

Frustratingly Simple Retrieval Improves Challenging, Reasoning-Intensive Benchmarks cites this paper.

Frustratingly Simple Retrieval Improves Challenging, Reasoning-Intensive Benchmarks ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T21:02:58.300557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 008a62c4-0b08-4baa-b7a6-220929a6c4dd · inbound

Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs cites this paper.

Towards Agentic RAG with Deep Reasoning: A Survey of RAG-Reasoning Systems in LLMs ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 2019

Resolution: unresolved; no resolver link, observed 2026-08-06T18:00:48.124033Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 22083f09-1e21-4c2f-a8e5-958bceee3a81 · inbound

Kimi K2: Open Agentic Intelligence cites this paper.

Kimi K2: Open Agentic Intelligence ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 70

Resolution: verified exact; arxiv_id, observed 2026-05-17T17:44:13.577137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 64186f76-6f6c-4130-a97c-02440d495a05 · inbound

ParallelSearch: Train your LLMs to Decompose Query and Search Sub-queries in Parallel with Reinforcement Learning cites this paper.

ParallelSearch: Train your LLMs to Decompose Query and Search Sub-queries in Parallel with Reinforcement Learning ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-05T21:12:11.902466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8f7c3d2-1a78-4583-892c-4749ddd15efa · inbound

SSRL: Self-Search Reinforcement Learning cites this paper.

SSRL: Self-Search Reinforcement Learning ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-05T20:17:12.061269Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f716f628-5cd9-4297-9902-194db5bb024b · inbound

Atom-Searcher: Enhancing Agentic Deep Research via Fine-Grained Atomic Thought Reward cites this paper.

Atom-Searcher: Enhancing Agentic Deep Research via Fine-Grained Atomic Thought Reward ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-05T19:21:52.228538Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d5138e2-3aec-4a06-852f-36d9df1b15c8 · inbound

Chain-of-Agents: End-to-End Agent Foundation Models via Multi-Agent Distillation and Agentic RL cites this paper.

Chain-of-Agents: End-to-End Agent Foundation Models via Multi-Agent Distillation and Agentic RL ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-05T23:57:34.744588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4aa972d9-522e-40aa-9b7d-71a8afa19c0e · inbound

MUA-RL: Multi-turn User-interacting Agent Reinforcement Learning for agentic tool use cites this paper.

MUA-RL: Multi-turn User-interacting Agent Reinforcement Learning for agentic tool use ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-05T16:22:51.580729Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 23b0208c-f8d2-48f6-aa1c-a6b1e0843da2 · inbound

Open Data Synthesis For Deep Research cites this paper.

Open Data Synthesis For Deep Research ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-05T13:45:12.880393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f2e6797-8687-4eb7-bee6-204b9943b5a4 · inbound

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey cites this paper.

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 291

Resolution: verified exact; local_arxiv, observed 2026-05-18T19:21:48.083190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation db41b4e9-bbba-4344-965c-9308351cd6bb · inbound

SafeSearch: Automated Red-Teaming of LLM-Based Search Agents cites this paper.

SafeSearch: Automated Red-Teaming of LLM-Based Search Agents ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-04T14:43:53.144738Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe3ef81d-2135-4304-b812-a8ab20d4c57c · inbound

Erase to Improve: Erasable Reinforcement Learning for Search-Augmented LLMs cites this paper.

Erase to Improve: Erasable Reinforcement Learning for Search-Augmented LLMs ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-05-18T11:11:18.243027Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d6204829-2ac6-47d5-9156-08232c55bac6 · inbound

Beyond Correctness: Rewarding Faithful Reasoning in Retrieval-Augmented Generation cites this paper.

Beyond Correctness: Rewarding Faithful Reasoning in Retrieval-Augmented Generation ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-04T09:50:49.763839Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 12b11eef-be01-4a5e-b4f1-bbca7197e53a · inbound

MemSearcher: Training LLMs to Reason, Search and Manage Memory via End-to-End Reinforcement Learning cites this paper.

MemSearcher: Training LLMs to Reason, Search and Manage Memory via End-to-End Reinforcement Learning ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-05-18T01:00:34.427606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 16849526-b346-475d-b034-e8691d606a4e · inbound

TeaRAG: A Token-Efficient Agentic Retrieval-Augmented Generation Framework cites this paper.

TeaRAG: A Token-Efficient Agentic Retrieval-Augmented Generation Framework ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-03T23:33:48.943481Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 73b02692-f7b7-4c8a-975d-e4e06361df7f · inbound

Agentic Reasoning for Large Language Models cites this paper.

Agentic Reasoning for Large Language Models ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 240

Resolution: verified exact; arxiv_id, observed 2026-05-17T17:44:13.577137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 3be6609d-e3ea-4139-b1a0-b2be409ba534 · inbound

CLEANER: Self-Purified Trajectories Boost Agentic Reinforcement Learning cites this paper.

CLEANER: Self-Purified Trajectories Boost Agentic Reinforcement Learning ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T09:01:50.680369Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b57a5ae9-9675-44ca-b679-12f0db223c91 · inbound

$\pi$-Play: Multi-Agent Self-Play via Privileged Self-Distillation without External Data cites this paper.

$\pi$-Play: Multi-Agent Self-Play via Privileged Self-Distillation without External Data ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-17T17:44:13.577137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5bcc6c5a-e832-4678-a87d-b6ae444c3fe8 · inbound

Democratizing Tool Learning with Environments Fully Simulated by a Free 8B Language Model cites this paper.

Democratizing Tool Learning with Environments Fully Simulated by a Free 8B Language Model ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 36

Resolution: verified exact; arxiv_id, observed 2026-05-17T17:44:13.577137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7439fd0e-d087-48cd-910f-f2b9a7c28086 · inbound

LiteResearcher: A Scalable Agentic RL Training Framework for Deep Research Agent cites this paper.

LiteResearcher: A Scalable Agentic RL Training Framework for Deep Research Agent ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-07-05T15:11:10.910914Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 51c56807-6fdc-4e42-85e4-c32c286a1916 · inbound

Negative Advantages Is a Double-Edged Sword: Calibrating advantages in GRPO for Search Agents cites this paper.

Negative Advantages Is a Double-Edged Sword: Calibrating advantages in GRPO for Search Agents ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-17T17:44:13.577137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 29d844e5-b155-48d3-84be-153d48aafdb8 · inbound

T$^2$PO: Uncertainty-Guided Exploration Control for Stable Multi-Turn Agentic Reinforcement Learning cites this paper.

T$^2$PO: Uncertainty-Guided Exploration Control for Stable Multi-Turn Agentic Reinforcement Learning ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-17T17:44:13.577137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b485c50b-9bf8-4e07-bb59-75be265f5cbf · inbound

LatentRAG: Latent Reasoning and Retrieval for Efficient Agentic RAG cites this paper.

LatentRAG: Latent Reasoning and Retrieval for Efficient Agentic RAG ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 78

Resolution: verified exact; arxiv_id, observed 2026-05-17T17:44:13.577137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bc9d25c7-4730-461e-8e89-f2e2fc2b278d · inbound

Learning CLI Agents with Structured Action Credit under Selective Observation cites this paper.

Learning CLI Agents with Structured Action Credit under Selective Observation ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-17T17:44:13.577137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation e43be5d5-2fe0-4908-97a7-d618bf063802 · inbound

AIPO: Learning to Reason from Active Interaction cites this paper.

AIPO: Learning to Reason from Active Interaction ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 61

Resolution: verified exact; arxiv_id, observed 2026-05-17T17:44:13.577137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 559bdfe8-c823-4392-ba6b-9cbcbc4324e2 · inbound

AIPO: Learning to Reason from Active Interaction cites this paper.

AIPO: Learning to Reason from Active Interaction ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 61

Resolution: verified exact; local_arxiv, observed 2026-05-19T18:07:42.331737Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bf02f1e9-a3dc-4062-ab52-6d3b0dd54dc8 · inbound

SearchSkill: Teaching LLMs to Use Search Tools with Evolving Skill Banks cites this paper.

SearchSkill: Teaching LLMs to Use Search Tools with Evolving Skill Banks ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-17T17:44:13.577137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d5de3ec6-3243-47ec-b011-7eadbf60298c · inbound

SearchSkill: Teaching LLMs to Use Search Tools with Evolving Skill Banks cites this paper.

SearchSkill: Teaching LLMs to Use Search Tools with Evolving Skill Banks ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-17T17:44:13.577137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d83ba957-1563-4da2-9816-76e7ac6c15b3 · inbound

SearchSkill: Teaching LLMs to Use Search Tools with Evolving Skill Banks cites this paper.

SearchSkill: Teaching LLMs to Use Search Tools with Evolving Skill Banks ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-07-01T13:35:46.393276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 199c9419-5388-4586-ae47-1dfce34e6936 · inbound

PiCA: Pivot-Based Credit Assignment for Search Agentic Reinforcement Learning cites this paper.

PiCA: Pivot-Based Credit Assignment for Search Agentic Reinforcement Learning ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-17T17:44:13.577137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation cdd216db-0d6b-4217-85ab-86b397374766 · inbound

PiCA: Pivot-Based Credit Assignment for Search Agentic Reinforcement Learning cites this paper.

PiCA: Pivot-Based Credit Assignment for Search Agentic Reinforcement Learning ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 30

Resolution: verified exact; arxiv_id, observed 2026-05-17T17:44:13.577137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4096f320-eb29-4b79-ba67-c64511a8a520 · inbound

CuSearch: Curriculum Rollout Sampling via Search Depth for Agentic RAG cites this paper.

CuSearch: Curriculum Rollout Sampling via Search Depth for Agentic RAG ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-17T17:44:13.577137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b710c942-97ec-45a3-af78-98468e34fed5 · inbound

CuSearch: Curriculum Rollout Sampling via Search Depth for Agentic RAG cites this paper.

CuSearch: Curriculum Rollout Sampling via Search Depth for Agentic RAG ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-17T17:44:13.577137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 37ee4269-071f-40d9-8e63-60562d2d8a6f · inbound

SkillGraph: Skill-Augmented Reinforcement Learning for Agents via Evolving Skill Graphs cites this paper.

SkillGraph: Skill-Augmented Reinforcement Learning for Agents via Evolving Skill Graphs ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 12

Resolution: metadata mismatch; arxiv_id, observed 2026-05-17T17:44:13.577137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 0fe2ae17-37ae-4eb8-bc64-1fa77e860d0c · inbound

Retrieval is Cheap, Show Me the Code: Executable Multi-Hop Reasoning for Retrieval-Augmented Generation cites this paper.

Retrieval is Cheap, Show Me the Code: Executable Multi-Hop Reasoning for Retrieval-Augmented Generation ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-17T17:44:13.577137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 6f814467-b9ee-4b49-b10a-c2e48f6ce90f · inbound

Scaling Retrieval-Augmented Reasoning with Parallel Search and Explicit Merging cites this paper.

Scaling Retrieval-Augmented Reasoning with Parallel Search and Explicit Merging ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-17T17:44:13.577137Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation bd76b198-0484-4797-a215-4a5064b3844a · inbound

Harnessing LLM Agents with Skill Programs cites this paper.

Harnessing LLM Agents with Skill Programs ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-05-20T11:28:14.390559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7db8312f-42c3-4704-a05b-20e072a41525 · inbound

Search-E1: Self-Distillation Drives Self-Evolution in Search-Augmented Reasoning cites this paper.

Search-E1: Self-Distillation Drives Self-Evolution in Search-Augmented Reasoning ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-05-22T06:11:09.200380Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation ef40330c-fca1-40a6-80d9-1858a719b5bc · inbound

Search-E1: Self-Distillation Drives Self-Evolution in Search-Augmented Reasoning cites this paper.

Search-E1: Self-Distillation Drives Self-Evolution in Search-Augmented Reasoning ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-06-30T17:24:56.781911Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 2a43c6e3-957f-420f-b0e5-e55efa8a6488 · inbound

When Denser Credit Is Not Enough: Evidence-Calibrated Policy Optimization for Long-Horizon LLM Agent Training cites this paper.

When Denser Credit Is Not Enough: Evidence-Calibrated Policy Optimization for Long-Horizon LLM Agent Training ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 47

Resolution: metadata mismatch; local_arxiv, observed 2026-07-02T12:16:56.822885Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 9dc86ad0-4ac1-4ba5-9ff1-3600745d6288 · inbound

Co-Evolving Skill Generation and Policy Optimization cites this paper.

Co-Evolving Skill Generation and Policy Optimization ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 93

Resolution: verified exact; local_arxiv, observed 2026-07-02T22:57:25.864373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7ae2de35-6a05-4370-bc23-5c95b372bfb7 · inbound

Toward Generalist Autonomous Research via Hypothesis-Tree Refinement cites this paper.

Toward Generalist Autonomous Research via Hypothesis-Tree Refinement ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 46

Resolution: verified exact; local_arxiv, observed 2026-06-27T09:40:47.097442Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b7e44d8e-843d-462d-ad2b-af0233ab18c2 · inbound

Qwen-AgentWorld: Language World Models for General Agents cites this paper.

Qwen-AgentWorld: Language World Models for General Agents ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 50

Resolution: verified exact; local_arxiv, observed 2026-07-04T17:09:59.265833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 4cab1aee-f6e4-48a5-b6e5-093351b2ae91 · inbound

DocArena: Turning Raw Documents into Controllable Training Environments for Document Search Agents cites this paper.

DocArena: Turning Raw Documents into Controllable Training Environments for Document Search Agents ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 44

Resolution: metadata mismatch; local_arxiv, observed 2026-06-29T12:53:26.563622Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 103ef9eb-cb44-456a-ad4d-66b729fe8c23 · inbound

R$^2$-Searcher: Calibrating Retrieval and Reasoning Boundaries for Agentic Search cites this paper.

R$^2$-Searcher: Calibrating Retrieval and Reasoning Boundaries for Agentic Search ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-06-30T00:34:05.139160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b32128c3-ab09-4cec-a14d-6bb8bec4572d · inbound

To Reason or to Fabricate: Reasoning Without Shortcuts via Hint-Anchored Pairwise Aggregation cites this paper.

To Reason or to Fabricate: Reasoning Without Shortcuts via Hint-Anchored Pairwise Aggregation ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 5

Resolution: metadata mismatch; local_arxiv, observed 2026-06-30T07:44:21.403934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 08704826-403a-4b63-952a-051391a0acb1 · inbound

As We May Search cites this paper.

As We May Search ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 52

Resolution: verified exact; local_arxiv, observed 2026-06-30T07:34:21.901873Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation b6e6b803-b3e4-4c18-b02e-95996769c389 · inbound

CheckRLM: Effective Knowledge-Thought Coherence Checking in Retrieval-Augmented Reasoning cites this paper.

CheckRLM: Effective Knowledge-Thought Coherence Checking in Retrieval-Augmented Reasoning ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 2

Resolution: metadata mismatch; local_arxiv, observed 2026-07-03T14:28:31.086964Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 5c063ef8-7448-4456-9872-05c7a28ec0d3 · inbound

Agent Reinforcement Learning via Pivotal-Aware Self-Feedback Retry cites this paper.

Agent Reinforcement Learning via Pivotal-Aware Self-Feedback Retry ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 12

Resolution: unresolved; no resolver link, observed 2026-07-12T00:33:06.488657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 76a4e2d2-bb8f-4746-9e5b-1a996670f524 · 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 ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 23

Resolution: verified exact; local_arxiv, observed 2026-07-08T13:04:56.726732Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 61c6a9c4-2f4c-43d9-9be1-39d977a9439b · inbound

STEC: Evidence Compression for Deep Search in Open-domain Multi-Hop QA cites this paper.

STEC: Evidence Compression for Deep Search in Open-domain Multi-Hop QA ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 13

Resolution: unresolved; no resolver link, observed 2026-07-14T09:13:24.763990Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a5977e5-3777-483c-80ee-a4e0d6a19add · inbound

DeepStress: Stress-Testing Deep Search Agents cites this paper.

DeepStress: Stress-Testing Deep Search Agents ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T03:23:38.114661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9aa12024-a25e-4e43-98da-c46e8c6782fd · inbound

TRACE: Turn-level Reward Assignment via Credit Estimation for Long-Horizon Agents cites this paper.

TRACE: Turn-level Reward Assignment via Credit Estimation for Long-Horizon Agents ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T03:10:51.595241Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cd6c5b9b-c9c2-421b-962b-f0f5f56503ae · 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 ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T09:45:49.601208Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2c1bf993-9c97-46b7-a545-892b5d0e4681 · inbound

PROGRESS: Coverage-guided RL to Train Search-augmented LLM Agent cites this paper.

PROGRESS: Coverage-guided RL to Train Search-augmented LLM Agent ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-06T00:37:24.709002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fac8333a-c316-4e68-9ba0-c7d119a48a70 · inbound

BiCAA: Bidirectional Credit Assignment for Search-Augmented Agent cites this paper.

BiCAA: Bidirectional Credit Assignment for Search-Augmented Agent ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T00:23:00.140200Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9c00a61b-45e2-4fd6-9c17-16930eff3e74 · inbound

Fetch-then-Explore: Decoupling Selection from Extraction over a Persistent Workspace for Search Agents cites this paper.

Fetch-then-Explore: Decoupling Selection from Extraction over a Persistent Workspace for Search Agents ZeroSearch: Incentivize the Search Capability of LLMs without Searching

Reference 133

Resolution: unresolved; no resolver link, observed 2026-08-04T15:12:55.859971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.