Kimi k1.5: Scaling Reinforcement Learning with LLMs | Paper Citation Record

Observation 6d708888-b4c7-438a-8898-fea272246142 · inbound

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities cites this paper.

Model Merging in LLMs, MLLMs, and Beyond: Methods, Theories, Applications and Opportunities Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 217

Resolution: verified exact; local_arxiv, observed 2026-05-17T22:16:04.609726Z

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Observation 8653bbd6-566a-47be-be2e-bcd8840e7dd3 · inbound

Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs cites this paper.

Do NOT Think That Much for 2+3=? On the Overthinking of o1-Like LLMs Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 220

Resolution: verified exact; local_arxiv, observed 2026-05-13T15:51:29.320931Z

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Observation 1aecb095-1905-4f80-bfd2-616e467a813c · inbound

Process Reinforcement through Implicit Rewards cites this paper.

Process Reinforcement through Implicit Rewards Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 75

Resolution: verified exact; local_arxiv, observed 2026-05-11T20:23:31.177274Z

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Observation c9711623-d425-4701-856b-75f9a58a784d · inbound

Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention cites this paper.

Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 77

Resolution: verified exact; local_arxiv, observed 2026-05-16T23:46:30.143868Z

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Observation a248f80a-a5e1-4951-93b9-13e1d36b7984 · inbound

Learning to Reason at the Frontier of Learnability cites this paper.

Learning to Reason at the Frontier of Learnability Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-05-23T02:42:26.188553Z

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Observation 3f941a00-a54c-4ee6-979b-bb26acf1bf0d · inbound

MoBA: Mixture of Block Attention for Long-Context LLMs cites this paper.

MoBA: Mixture of Block Attention for Long-Context LLMs Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-05-16T06:15:46.159064Z

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Observation b1de12cd-fede-4117-9244-e85470f4b94a · inbound

From System 1 to System 2: A Survey of Reasoning Large Language Models cites this paper.

From System 1 to System 2: A Survey of Reasoning Large Language Models Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 266

Resolution: verified exact; local_arxiv, observed 2026-05-13T01:36:24.471179Z

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Observation 48d3ba51-6ecb-458c-842b-9ce19e4cb341 · inbound

Visual-RFT: Visual Reinforcement Fine-Tuning cites this paper.

Visual-RFT: Visual Reinforcement Fine-Tuning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-05-13T22:16:16.593843Z

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Observation 61f2d32a-2f4c-4f4a-a371-a3c811f9c7ee · inbound

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

R1-Searcher: Incentivizing the Search Capability in LLMs via Reinforcement Learning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-13T18:37:17.752362Z

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Observation cd497d56-4312-4bd4-8d76-2b089ab49a81 · inbound

LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL cites this paper.

LMM-R1: Empowering 3B LMMs with Strong Reasoning Abilities Through Two-Stage Rule-Based RL Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 69

Resolution: verified exact; local_arxiv, observed 2026-05-16T15:15:46.423344Z

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Observation 89102e30-a3ca-44a5-9881-58c3533f5078 · inbound

Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscation cites this paper.

Monitoring Reasoning Models for Misbehavior and the Risks of Promoting Obfuscation Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-05-21T07:24:12.918474Z

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Observation 71a9e7e7-0dce-4ccb-a69d-5eaa52a1f685 · inbound

Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey cites this paper.

Multimodal Chain-of-Thought Reasoning: A Comprehensive Survey Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 269

Resolution: verified exact; local_arxiv, observed 2026-05-15T17:18:53.598843Z

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Observation b1796957-ff78-4880-9a77-b36772e2866b · inbound

R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization cites this paper.

R1-VL: Learning to Reason with Multimodal Large Language Models via Step-wise Group Relative Policy Optimization Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-05-16T15:04:22.887467Z

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Observation ed0712cc-0800-4619-b28c-bdfa039ab602 · inbound

DAPO: An Open-Source LLM Reinforcement Learning System at Scale cites this paper.

DAPO: An Open-Source LLM Reinforcement Learning System at Scale Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-05-22T23:35:13.448053Z

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Observation cb2847bd-bbcb-4fdc-aa5a-2a26c3025500 · inbound

Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models cites this paper.

Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 171

Resolution: verified exact; local_arxiv, observed 2026-05-14T01:29:56.903440Z

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Observation 4bb04e3b-a2db-468c-a636-90096ca97130 · inbound

ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning cites this paper.

ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-05-16T15:48:34.739216Z

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Observation e319ed2a-463a-442f-8c6e-cbee2b25a1e7 · inbound

Video-R1: Reinforcing Video Reasoning in MLLMs cites this paper.

Video-R1: Reinforcing Video Reasoning in MLLMs Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-05-12T09:43:00.431238Z

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Observation 5f747e53-c4ee-49ba-b0f1-0f2fe085ca78 · inbound

Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model cites this paper.

Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 7

Resolution: verified exact; local_arxiv, observed 2026-05-12T21:59:02.252910Z

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Observation 095a3046-4b55-4e32-8369-ad3a6e39dbe8 · inbound

SpaceR: Reinforcing MLLMs in Video Spatial Reasoning cites this paper.

SpaceR: Reinforcing MLLMs in Video Spatial Reasoning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 31

Resolution: verified exact; local_arxiv, observed 2026-05-15T15:18:43.812944Z

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Observation 40925960-7ef7-471c-996d-d81765b6e95d · inbound

OpenCodeReasoning: Advancing Data Distillation for Competitive Coding cites this paper.

OpenCodeReasoning: Advancing Data Distillation for Competitive Coding Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 19

Resolution: metadata mismatch; local_arxiv, observed 2026-05-17T19:21:42.165575Z

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Observation 2d2beea4-e50d-438e-acf1-f56f250e6438 · inbound

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems cites this paper.

Advances and Challenges in Foundation Agents: From Brain-Inspired Intelligence to Evolutionary, Collaborative, and Safe Systems Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 141

Resolution: verified exact; local_arxiv, observed 2026-05-22T21:42:10.609516Z

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Observation 6e7fddc5-25e0-44ad-a184-5248ab255269 · inbound

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

DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 4

Resolution: verified exact; local_arxiv, observed 2026-05-16T19:58:58.986839Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 84ff15ce-ebef-48c2-9808-cad69e8cdd71 · inbound

VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks cites this paper.

VAPO: Efficient and Reliable Reinforcement Learning for Advanced Reasoning Tasks Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 26

Resolution: verified exact; local_arxiv, observed 2026-05-13T09:36:04.786222Z

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Observation c409a1c8-e932-48b3-aa22-b95800169138 · inbound

VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning cites this paper.

VideoChat-R1: Enhancing Spatio-Temporal Perception via Reinforcement Fine-Tuning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-05-15T20:56:07.862745Z

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Observation 54e9dd96-825c-4069-a733-e74f78df2ff5 · inbound

ReTool: Reinforcement Learning for Strategic Tool Use in LLMs cites this paper.

ReTool: Reinforcement Learning for Strategic Tool Use in LLMs Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-05-13T18:42:39.102889Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation e0edcb6b-d345-46ca-8a7e-518e59e634c0 · inbound

Reinforcement Learning from Human Feedback cites this paper.

Reinforcement Learning from Human Feedback Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 145

Resolution: verified exact; local_arxiv, observed 2026-05-22T19:32:01.341300Z

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Observation 1b512694-8ec9-43ea-be6c-cd971f4682f6 · inbound

ToolRL: Reward is All Tool Learning Needs cites this paper.

ToolRL: Reward is All Tool Learning Needs Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-05-14T00:26:48.542087Z

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Observation e976d878-afad-4ede-b44f-1a7396f5fc7e · inbound

Learning to Reason under Off-Policy Guidance cites this paper.

Learning to Reason under Off-Policy Guidance Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-15T23:17:02.761555Z

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Observation b7736300-0613-4043-9c1e-bd38fc37a277 · inbound

Kimi-Audio Technical Report cites this paper.

Kimi-Audio Technical Report Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 65

Resolution: verified exact; local_arxiv, observed 2026-05-11T19:21:27.056552Z

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Observation 5411608b-f66e-48e2-bd8e-c4f42fd216c6 · inbound

Reinforcement Learning for Reasoning in Large Language Models with One Training Example cites this paper.

Reinforcement Learning for Reasoning in Large Language Models with One Training Example Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-15T19:51:04.852051Z

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Observation 7d51f35e-89ac-4b36-ade0-9ed494a3c128 · inbound

Phi-4-reasoning Technical Report cites this paper.

Phi-4-reasoning Technical Report Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 54

Resolution: verified exact; local_arxiv, observed 2026-05-17T03:40:25.840520Z

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Observation e865d535-2f92-40a2-8330-4064c2c4a11a · inbound

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

Group-in-Group Policy Optimization for LLM Agent Training Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 56

Resolution: verified exact; local_arxiv, observed 2026-05-11T09:15:08.521515Z

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Observation 666e2039-f190-465b-a673-347e31f827fc · inbound

DeepEyes: Incentivizing "Thinking with Images" via Reinforcement Learning cites this paper.

DeepEyes: Incentivizing "Thinking with Images" via Reinforcement Learning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 22

Resolution: verified exact; local_arxiv, observed 2026-05-11T14:42:57.059361Z

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Observation a42a63b1-4bfd-4501-bbc5-69b026968ef4 · inbound

TemplateRL: Structured Template-Guided Reinforcement Learning for LLM Reasoning cites this paper.

TemplateRL: Structured Template-Guided Reinforcement Learning for LLM Reasoning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-22T13:41:36.193441Z

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Observation a9dca9a3-4128-4376-acc7-12a18e9f0db2 · inbound

Universal Reasoner: A Single, Composable Plug-and-Play Reasoner for Frozen LLMs cites this paper.

Universal Reasoner: A Single, Composable Plug-and-Play Reasoner for Frozen LLMs Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 37

Resolution: verified exact; local_arxiv, observed 2026-05-22T01:20:52.144708Z

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Observation 934b28bb-4b84-43ab-90b0-434af68644ec · inbound

Skywork Open Reasoner 1 Technical Report cites this paper.

Skywork Open Reasoner 1 Technical Report Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 24

Resolution: verified exact; local_arxiv, observed 2026-05-17T04:26:47.346012Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3cb35132-a5a3-451f-82d5-7527f8c1d3e8 · inbound

Grounded Reinforcement Learning for Visual Reasoning cites this paper.

Grounded Reinforcement Learning for Visual Reasoning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 60

Resolution: verified exact; local_arxiv, observed 2026-05-22T01:05:52.126115Z

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Observation a4fc95c6-5257-48ff-b5b5-465603ebac42 · inbound

Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning cites this paper.

Beyond the 80/20 Rule: High-Entropy Minority Tokens Drive Effective Reinforcement Learning for LLM Reasoning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-05-12T12:12:08.952726Z

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Observation c56f9962-2490-41a2-8bd5-18ab8b5d60d3 · inbound

MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention cites this paper.

MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-05-12T09:28:16.396386Z

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Observation a166b24c-de5e-4551-95c1-ce9de0be2e20 · inbound

Steering Your Diffusion Policy with Latent Space Reinforcement Learning cites this paper.

Steering Your Diffusion Policy with Latent Space Reinforcement Learning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-05-17T21:55:46.319560Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation b6c0fd85-71fb-496c-8b74-bfa8053f38ed · inbound

LongWriter-Zero: Mastering Ultra-Long Text Generation via Reinforcement Learning cites this paper.

LongWriter-Zero: Mastering Ultra-Long Text Generation via Reinforcement Learning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-05-19T07:52:09.288180Z

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Observation 72d823a9-7154-4c18-9dbd-b136a94a75e3 · inbound

MMSearch-R1: Incentivizing LMMs to Search cites this paper.

MMSearch-R1: Incentivizing LMMs to Search Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 58

Resolution: verified exact; local_arxiv, observed 2026-05-16T15:27:04.306580Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 0e63ede9-b656-4c97-8415-86db9d5cda0f · inbound

Improving the Reasoning of Multi-Image Grounding in MLLMs via Reinforcement Learning cites this paper.

Improving the Reasoning of Multi-Image Grounding in MLLMs via Reinforcement Learning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 35

Resolution: verified exact; local_arxiv, observed 2026-05-19T06:52:08.002507Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation f72f700c-fb04-4146-92b8-ef88c2b4f01a · inbound

MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent cites this paper.

MemAgent: Reshaping Long-Context LLM with Multi-Conv RL-based Memory Agent Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 53

Resolution: verified exact; local_arxiv, observed 2026-05-15T11:17:24.475823Z

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Observation 45a08cdb-c93e-46ad-a4d7-fa26f212ad43 · inbound

Stabilizing Knowledge, Promoting Reasoning: Dual-Token Constraints for RLVR cites this paper.

Stabilizing Knowledge, Promoting Reasoning: Dual-Token Constraints for RLVR Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-05-21T23:24:26.296842Z

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Observation 64a46139-cb99-4a58-be2c-d2cc0558fd1c · inbound

Kimi K2: Open Agentic Intelligence cites this paper.

Kimi K2: Open Agentic Intelligence Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-10T17:58:27.800589Z

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Observation cdc8a545-7cdc-4b37-8d5b-ca1b96c3f2dc · inbound

ChemDFM-R: A Chemical Reasoning LLM Enhanced with Atomized Chemical Knowledge cites this paper.

ChemDFM-R: A Chemical Reasoning LLM Enhanced with Atomized Chemical Knowledge Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 18

Resolution: verified exact; local_arxiv, observed 2026-05-19T03:32:01.610665Z

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Observation e437c7e8-593e-4319-abf4-4ed102200f61 · inbound

RL-PLUS: Countering Capability Boundary Collapse of LLMs in Reinforcement Learning with Hybrid-policy Optimization cites this paper.

RL-PLUS: Countering Capability Boundary Collapse of LLMs in Reinforcement Learning with Hybrid-policy Optimization Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 11

Resolution: verified exact; local_arxiv, observed 2026-05-19T01:16:57.045584Z

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No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.

Observation 3b5fe955-a88c-408b-91b0-14dc6f1ddaee · inbound

Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens cites this paper.

Is Chain-of-Thought Reasoning of LLMs a Mirage? A Data Distribution Lens Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-05-19T01:21:58.048901Z

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 79a5917e-3321-462c-9d62-c4859bbe21ea · inbound

ReasoningGuard: Safeguarding Large Reasoning Models with Inference-time Safety Aha Moments cites this paper.

ReasoningGuard: Safeguarding Large Reasoning Models with Inference-time Safety Aha Moments Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-05-19T01:02:54.944572Z

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 495ab55e-7b60-4b90-917a-3100a15e9bc2 · inbound

EvoCoT: Overcoming the Exploration Bottleneck in Reinforcement Learning cites this paper.

EvoCoT: Overcoming the Exploration Bottleneck in Reinforcement Learning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 14

Resolution: verified exact; local_arxiv, observed 2026-05-18T23:56:54.995146Z

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 5343a5ab-74e2-4848-9367-89c845b1b52b · inbound

Pruning Long Chain-of-Thought of Large Reasoning Models via Small-Scale Preference Optimization cites this paper.

Pruning Long Chain-of-Thought of Large Reasoning Models via Small-Scale Preference Optimization Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-05-18T22:31:53.217502Z

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 16b82acc-34d1-4641-88e5-503afeb4c90f · inbound

UAV-VL-R1: Generalizing Vision-Language Models via Supervised Fine-Tuning and Multi-Stage GRPO for UAV Visual Reasoning cites this paper.

UAV-VL-R1: Generalizing Vision-Language Models via Supervised Fine-Tuning and Multi-Stage GRPO for UAV Visual Reasoning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 9

Resolution: verified exact; local_arxiv, observed 2026-05-18T22:21:53.285753Z

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 fa45072b-0a9e-46aa-959d-8a7e4d6ac8f6 · inbound

Depth-Breadth Synergy in RLVR: Unlocking LLM Reasoning Gains with Adaptive Exploration cites this paper.

Depth-Breadth Synergy in RLVR: Unlocking LLM Reasoning Gains with Adaptive Exploration Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-05-18T22:36:53.724095Z

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 d9c33360-1dc0-4ee4-a6b2-ae2f6bebbbed · inbound

Embodied-R1: Reinforced Embodied Reasoning for General Robotic Manipulation cites this paper.

Embodied-R1: Reinforced Embodied Reasoning for General Robotic Manipulation Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-05-18T22:06:51.602113Z

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 634e0119-9e7c-4483-b5ff-2b2d75fbe67f · inbound

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

The Landscape of Agentic Reinforcement Learning for LLMs: A Survey Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 225

Resolution: verified exact; local_arxiv, observed 2026-05-18T19:21:48.723125Z

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 9537a6b7-3ac1-4c0c-bcc5-e1fa48a06faf · inbound

Self-Aligned Reward: Towards Effective and Efficient Reasoners cites this paper.

Self-Aligned Reward: Towards Effective and Efficient Reasoners Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 44

Resolution: verified exact; local_arxiv, observed 2026-05-18T18:31:44.464150Z

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 ff25f9ea-9d50-4bec-a63e-616b03eb82c8 · inbound

Mini-o3: Scaling Up Reasoning Patterns and Interaction Turns for Visual Search cites this paper.

Mini-o3: Scaling Up Reasoning Patterns and Interaction Turns for Visual Search Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 36

Resolution: verified exact; local_arxiv, observed 2026-05-18T01:17:55.578434Z

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 8297df1d-caa8-46aa-9253-1e0b93e05d42 · inbound

Positional Encoding via Token-Aware Phase Attention cites this paper.

Positional Encoding via Token-Aware Phase Attention Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-05-18T16:21:36.687422Z

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 74123168-75ff-4d0c-ad17-f26f70ac480d · inbound

ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program Evolution cites this paper.

ShinkaEvolve: Towards Open-Ended And Sample-Efficient Program Evolution Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 129

Resolution: verified exact; local_arxiv, observed 2026-05-16T13:58:58.892906Z

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 e46a6aa9-4bfd-4f67-82dd-d0f155e4dc36 · inbound

Mixture-of-Visual-Thoughts: Exploring Context-Adaptive Reasoning Mode Selection for General Visual Reasoning cites this paper.

Mixture-of-Visual-Thoughts: Exploring Context-Adaptive Reasoning Mode Selection for General Visual Reasoning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 16

Resolution: verified exact; local_arxiv, observed 2026-05-18T13:36:25.170186Z

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 454907b5-d3db-4382-ac25-dcc3279a8f0a · inbound

Mitigating Visual Context Degradation in Large Multimodal Models: A Training-Free Decoupled Agentic Framework cites this paper.

Mitigating Visual Context Degradation in Large Multimodal Models: A Training-Free Decoupled Agentic Framework Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-05-18T12:32:36.422959Z

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 652fea36-7d7b-4267-b529-c2c7a6595417 · inbound

Structured In-context Environment Scaling for Large Language Model Reasoning cites this paper.

Structured In-context Environment Scaling for Large Language Model Reasoning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-05-18T12:26:22.286187Z

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 1edd9de9-3563-4cfd-909c-e5cc69260978 · inbound

AdaThink-Med: Optimizing Inference-Time Compute for Medical Reasoning via Uncertainty Quantification cites this paper.

AdaThink-Med: Optimizing Inference-Time Compute for Medical Reasoning via Uncertainty Quantification Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-04T13:51:52.132024Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e74cf059-1eb6-41ef-94ac-0172c31491b6 · inbound

Selective Expert Guidance for Effective and Diverse Exploration in Reinforcement Learning of LLMs cites this paper.

Selective Expert Guidance for Effective and Diverse Exploration in Reinforcement Learning of LLMs Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-04T11:33:54.857546Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8462615-fa77-4b81-901a-61b7829f41f3 · inbound

EEPO: Exploration-Enhanced Policy Optimization via Sample-Then-Forget cites this paper.

EEPO: Exploration-Enhanced Policy Optimization via Sample-Then-Forget Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-05-18T08:56:08.668075Z

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 4547ea09-eeec-48c5-af86-c79ed85c1dd6 · inbound

SCOPE-RL: Stable and Quantitative Control of Policy Entropy in RL Post-Training cites this paper.

SCOPE-RL: Stable and Quantitative Control of Policy Entropy in RL Post-Training Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 17

Resolution: verified exact; local_arxiv, observed 2026-05-21T20:30:35.502233Z

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 ddc515c0-7ad1-46d2-b913-dab5683e33b3 · inbound

Which Heads Matter for Reasoning? RL-Guided KV Cache Compression cites this paper.

Which Heads Matter for Reasoning? RL-Guided KV Cache Compression Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T10:50:10.536612Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 24792794-07c6-4499-91f7-1e8a82d5f00f · inbound

On the optimization dynamics of RLVR: Gradient gap and step size thresholds cites this paper.

On the optimization dynamics of RLVR: Gradient gap and step size thresholds Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 19

Resolution: verified exact; local_arxiv, observed 2026-05-18T08:36:07.311739Z

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 c63b186b-05fb-47b6-a7b8-365e099d1d7e · inbound

CLARity: Reasoning Consistency Alone Can Teach Reinforced Experts cites this paper.

CLARity: Reasoning Consistency Alone Can Teach Reinforced Experts Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T10:40:45.717755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 81ecfa51-61e4-48fe-a525-8bfa6dc7a1a4 · inbound

Don't Tell the Answer, Truly Guide the Reasoning During RL Rollouts cites this paper.

Don't Tell the Answer, Truly Guide the Reasoning During RL Rollouts Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-04T10:39:28.356959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8adb4402-be2c-45d4-8862-6d61638836ac · inbound

Rethinking Entropy Interventions in RLVR: An Entropy Change Perspective cites this paper.

Rethinking Entropy Interventions in RLVR: An Entropy Change Perspective Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 20

Resolution: verified exact; local_arxiv, observed 2026-05-18T07:41:03.227703Z

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 1b29aa27-7954-4bf4-8343-a987911f4dc4 · inbound

Attention Illuminates LLM Reasoning: The Preplan-and-Anchor Rhythm Enables Fine-Grained Policy Optimization cites this paper.

Attention Illuminates LLM Reasoning: The Preplan-and-Anchor Rhythm Enables Fine-Grained Policy Optimization Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-04T09:48:09.075731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e38770a1-69dd-46fe-9f6b-2e2af7817e33 · inbound

RoboGPT-R1: Enhancing Robot Task Planning with Reinforcement Learning cites this paper.

RoboGPT-R1: Enhancing Robot Task Planning with Reinforcement Learning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-04T09:33:40.825945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6250a448-94fb-4daf-90d1-7da7064947fe · inbound

Investigating Thinking Behaviours of Reasoning-Based Language Models for Social Bias Mitigation cites this paper.

Investigating Thinking Behaviours of Reasoning-Based Language Models for Social Bias Mitigation Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 16

Resolution: metadata mismatch; local_arxiv, observed 2026-05-18T07:01:01.665281Z

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 d269007c-82a1-4721-bcf9-8589d34c8e8a · inbound

Explainability of Large Language Models: Opportunities and Challenges toward Generating Trustworthy Explanations cites this paper.

Explainability of Large Language Models: Opportunities and Challenges toward Generating Trustworthy Explanations Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T09:08:50.685982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c65c24ce-5113-413c-8eab-149900b53faf · inbound

NoisyGRPO: Incentivizing Multimodal CoT Reasoning via Noise Injection and Bayesian Estimation cites this paper.

NoisyGRPO: Incentivizing Multimodal CoT Reasoning via Noise Injection and Bayesian Estimation Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 49

Resolution: verified exact; local_arxiv, observed 2026-05-18T04:40:53.038957Z

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 bfe9ebae-13de-45fb-888f-7bc8b4c40af2 · inbound

When Fewer Layers Break More Chains: Layer Pruning Harms Test-Time Scaling in LLMs cites this paper.

When Fewer Layers Break More Chains: Layer Pruning Harms Test-Time Scaling in LLMs Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-04T08:11:52.604380Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ee9956e-6d00-4ef4-aa60-664224a7a13f · inbound

Kimi Linear: An Expressive, Efficient Attention Architecture cites this paper.

Kimi Linear: An Expressive, Efficient Attention Architecture Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 98

Resolution: verified exact; local_arxiv, observed 2026-05-13T23:49:10.836472Z

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 890e057e-89b8-4774-8bee-3f1ad332755e · inbound

Sharpness-Guided Group Relative Policy Optimization via Probability Shaping cites this paper.

Sharpness-Guided Group Relative Policy Optimization via Probability Shaping Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-05-18T03:12:22.304257Z

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 b0dc3d5f-5cf6-4b9b-ba7f-6fd593e0749e · inbound

RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environments cites this paper.

RLVE: Scaling Up Reinforcement Learning for Language Models with Adaptive Verifiable Environments Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-03T23:08:06.494187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e32b2ea2-1a58-457f-979f-3b3d0eeae31a · inbound

MURPHY: Feedback-Aware GRPO with Retrospective Credit Assignment for Multi-Turn Code Generation cites this paper.

MURPHY: Feedback-Aware GRPO with Retrospective Credit Assignment for Multi-Turn Code Generation Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 21

Resolution: verified exact; local_arxiv, observed 2026-05-17T23:15:26.675857Z

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 09a89a1e-676c-4fb0-8bf3-f3927607c82b · inbound

Seer: Online Context Learning for Fast Synchronous LLM Reinforcement Learning cites this paper.

Seer: Online Context Learning for Fast Synchronous LLM Reinforcement Learning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 40

Resolution: verified exact; local_arxiv, observed 2026-05-17T20:40:14.535928Z

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 4fdfebe1-4ffc-406b-ab43-1fd957c17927 · inbound

Chinese Short-Form Creative Content Generation via Explanation-Oriented Multi-Objective Optimization cites this paper.

Chinese Short-Form Creative Content Generation via Explanation-Oriented Multi-Objective Optimization Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 87

Resolution: verified exact; local_arxiv, observed 2026-05-17T20:52:06.049547Z

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 14a228b8-0e3d-44e5-aee9-78dc66e2842c · inbound

Asking like Socrates: Socrates helps VLMs understand remote sensing images cites this paper.

Asking like Socrates: Socrates helps VLMs understand remote sensing images Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-05-17T04:59:04.357639Z

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 6dcaa061-8b6f-4c7c-ae79-ed424a7cf4af · inbound

GENIUS: An Agentic AI Framework for Autonomous Design and Execution of Simulation Protocols cites this paper.

GENIUS: An Agentic AI Framework for Autonomous Design and Execution of Simulation Protocols Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-05-25T07:55:33.216934Z

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 d8f481df-406a-44b2-8ce7-2945308d9dbc · inbound

MOA: Multi-Objective Alignment for Role-Playing Agents cites this paper.

MOA: Multi-Objective Alignment for Role-Playing Agents Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 6

Resolution: verified exact; local_arxiv, observed 2026-05-16T23:18:40.165466Z

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 3a0019ae-4485-4311-a5ff-804f88b5e82c · inbound

AP-BMM: Approximating Capability-Cost Pareto Sets of LLMs via Asynchronous Prior-Guided Bayesian Model Merging cites this paper.

AP-BMM: Approximating Capability-Cost Pareto Sets of LLMs via Asynchronous Prior-Guided Bayesian Model Merging Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 15

Resolution: verified exact; local_arxiv, observed 2026-05-16T23:21:21.635514Z

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 8909b1bc-07cd-4c06-b838-24e173dc2860 · inbound

AP-BMM: Approximating Capability-Cost Pareto Sets of LLMs via Asynchronous Prior-Guided Bayesian Model Merging cites this paper.

AP-BMM: Approximating Capability-Cost Pareto Sets of LLMs via Asynchronous Prior-Guided Bayesian Model Merging Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-03T17:25:19.818835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbb83637-2f4a-4ae4-9a38-9c349983cf06 · inbound

Boosting RL-Based Visual Reasoning with Selective Adversarial Entropy Intervention cites this paper.

Boosting RL-Based Visual Reasoning with Selective Adversarial Entropy Intervention Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T17:15:17.681302Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7420bf05-d9d8-4cdc-b062-a7fee0a143f1 · inbound

AGAPI-Agents: An Open-Access Agentic AI Platform for Accelerated Materials Design on AtomGPT.org cites this paper.

AGAPI-Agents: An Open-Access Agentic AI Platform for Accelerated Materials Design on AtomGPT.org Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-03T16:56:24.470919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91db51b0-4d4e-4b45-9ca0-0c52ebdd393b · inbound

NeoAMT: Neologism-Aware Agentic Machine Translation with Reinforcement Learning cites this paper.

NeoAMT: Neologism-Aware Agentic Machine Translation with Reinforcement Learning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 5

Resolution: verified exact; local_arxiv, observed 2026-05-16T16:43:06.450909Z

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 2015259b-08df-4c51-9892-23bf62ba4781 · inbound

NeoAMT: Neologism-Aware Agentic Machine Translation with Reinforcement Learning cites this paper.

NeoAMT: Neologism-Aware Agentic Machine Translation with Reinforcement Learning Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 2025

Resolution: unresolved; no resolver link, observed 2026-08-03T12:16:37.971746Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 98645355-1915-40ff-b637-5116521dd9aa · inbound

GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization cites this paper.

GDPO: Group reward-Decoupled Normalization Policy Optimization for Multi-reward RL Optimization Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-05-15T05:31:55.913738Z

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 e4b2c9cd-ba6e-4513-bdae-886c1419e46a · inbound

Mid-Think: Training-Free Intermediate-Budget Reasoning via Token-Level Triggers cites this paper.

Mid-Think: Training-Free Intermediate-Budget Reasoning via Token-Level Triggers Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-03T11:16:00.426231Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92d11159-1771-498d-947f-e2badaf31425 · inbound

Mimic Human Cognition, Master Multi-Image Reasoning: A Meta-Action Framework for Enhanced Visual Understanding cites this paper.

Mimic Human Cognition, Master Multi-Image Reasoning: A Meta-Action Framework for Enhanced Visual Understanding Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-03T11:13:16.913136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd878a42-f3c8-4de1-8349-2ca61243d6c6 · inbound

Agentic Reasoning for Large Language Models cites this paper.

Agentic Reasoning for Large Language Models Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 241

Resolution: verified exact; local_arxiv, observed 2026-05-17T15:14:26.329587Z

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 d5bdd606-2987-4e21-b619-42fbc18bb306 · inbound

StaleFlow: Staleness-Aware Data Management for Mitigating Data Skewness in Fully Disaggregated RL Post-Training cites this paper.

StaleFlow: Staleness-Aware Data Management for Mitigating Data Skewness in Fully Disaggregated RL Post-Training Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-04T06:25:53.654690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 919d3b82-5613-427c-b3c8-cae35a7f5003 · inbound

ConPress: Learning Efficient Reasoning from Multi-Question Contextual Pressure cites this paper.

ConPress: Learning Efficient Reasoning from Multi-Question Contextual Pressure Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T05:43:54.629963Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Small Generalizable Prompt Predictive Models Can Steer Efficient RL Post-Training of Large Reasoning Models cites this paper.

Small Generalizable Prompt Predictive Models Can Steer Efficient RL Post-Training of Large Reasoning Models Kimi k1.5: Scaling Reinforcement Learning with LLMs

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-05-21T14:10:13.072868Z

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