ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models | Paper Citation Record

Observation 262fd3c7-4766-406c-81c5-c18a13cbfd8b · inbound

HybridFlow: A Flexible and Efficient RLHF Framework cites this paper.

HybridFlow: A Flexible and Efficient RLHF Framework ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 49

Resolution: verified exact; arxiv_id, observed 2026-05-11T07:53:38.919778Z

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Observation cacf610b-102d-46f0-8143-b28a42d80033 · inbound

Process Reinforcement through Implicit Rewards cites this paper.

Process Reinforcement through Implicit Rewards ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 97

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:23:31.123445Z

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ViaRL: Adaptive Temporal Grounding via Visual Iterated Amplification Reinforcement Learning cites this paper.

ViaRL: Adaptive Temporal Grounding via Visual Iterated Amplification Reinforcement Learning ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 14

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Thompson Sampling in Online RLHF with General Function Approximation cites this paper.

Thompson Sampling in Online RLHF with General Function Approximation ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 24

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Observation b3b842df-d41e-4957-991c-f0ea6963c5f2 · inbound

Response-Level Rewards Are All You Need for Online Reinforcement Learning in LLMs: A Mathematical Perspective cites this paper.

Response-Level Rewards Are All You Need for Online Reinforcement Learning in LLMs: A Mathematical Perspective ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 11

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Observation d6b7d1d8-ef1f-423c-9de4-6e08705465b3 · inbound

DeepForm: Reasoning Large Language Model for Communication System Formulation cites this paper.

DeepForm: Reasoning Large Language Model for Communication System Formulation ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 5

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Observation 8ce80491-f06c-4686-80c5-003108961082 · inbound

Formalizing Learning from Language Feedback with Provable Guarantees cites this paper.

Formalizing Learning from Language Feedback with Provable Guarantees ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 22

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Observation 6cb29d71-2aa2-4135-8315-01a3eedbb761 · inbound

Reasoner for Real-World Event Detection: Scaling Reinforcement Learning via Adaptive Perplexity-Aware Sampling Strategy cites this paper.

Reasoner for Real-World Event Detection: Scaling Reinforcement Learning via Adaptive Perplexity-Aware Sampling Strategy ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T21:02:38.690014Z

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Observation bf6ead8d-9d7c-45c8-babe-ddda1bd24138 · inbound

Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training cites this paper.

Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 22

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Observation 62ef0cf6-7c98-4fcd-90de-0686f7a6e8d3 · inbound

Supervised Fine Tuning on Curated Data is Reinforcement Learning (and can be improved) cites this paper.

Supervised Fine Tuning on Curated Data is Reinforcement Learning (and can be improved) ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T16:44:46.084746Z

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Observation c6447613-bc92-4abc-8e7b-a10de149a9dd · inbound

Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges cites this paper.

Alignment and Safety in Large Language Models: Safety Mechanisms, Training Paradigms, and Emerging Challenges ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 236

Resolution: unresolved; no resolver link, observed 2026-08-06T14:13:07.156651Z

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Observation b485999e-b648-4a9f-9df2-dd6221a6a049 · inbound

QueryBandits for Hallucination Mitigation: Exploiting Semantic Features for No-Regret Rewriting cites this paper.

QueryBandits for Hallucination Mitigation: Exploiting Semantic Features for No-Regret Rewriting ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-05T17:39:23.364289Z

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Observation c232298c-300c-4099-974f-f48cb920172d · inbound

A Survey of Reinforcement Learning for Large Reasoning Models cites this paper.

A Survey of Reinforcement Learning for Large Reasoning Models ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 297

Resolution: metadata mismatch; arxiv_id, observed 2026-05-18T00:02:24.813875Z

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Observation 144fb14d-6962-4659-acae-7b7eda5d96b0 · inbound

Inpainting-Guided Policy Optimization for Diffusion Large Language Models cites this paper.

Inpainting-Guided Policy Optimization for Diffusion Large Language Models ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-04T17:57:46.988775Z

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Variance-Aware Baselines and Adaptive Learning Rates for Reinforcement Learning with Verifiable Rewards cites this paper.

Variance-Aware Baselines and Adaptive Learning Rates for Reinforcement Learning with Verifiable Rewards ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-03T19:38:21.049607Z

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Observation cd5d6fde-b090-4875-99ab-5af041d96c5e · inbound

Variance-Aware Baselines and Adaptive Learning Rates for Reinforcement Learning with Verifiable Rewards cites this paper.

Variance-Aware Baselines and Adaptive Learning Rates for Reinforcement Learning with Verifiable Rewards ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T06:47:16.815569Z

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Observation 5dbfeab3-23f4-4704-9446-35d3bdb5c8ca · inbound

Image Diffusion Preview with Consistency Solver cites this paper.

Image Diffusion Preview with Consistency Solver ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-16T21:43:34.676931Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 3f8af7fc-181a-40bd-8b32-1bbb3796e112 · inbound

Learning Decentralized LLM Collaboration with Multi-Agent Actor Critic cites this paper.

Learning Decentralized LLM Collaboration with Multi-Agent Actor Critic ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-16T09:50:49.367579Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5b776141-93a9-4d6c-83c9-d12f843224da · inbound

Learning Decentralized LLM Collaboration with Multi-Agent Actor Critic cites this paper.

Learning Decentralized LLM Collaboration with Multi-Agent Actor Critic ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-03T06:46:39.414831Z

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Observation 13264c45-0831-4b7d-90fd-ce0557c6a033 · inbound

Lightning OPD: Efficient Post-Training for Large Reasoning Models with Offline On-Policy Distillation cites this paper.

Lightning OPD: Efficient Post-Training for Large Reasoning Models with Offline On-Policy Distillation ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:01:08.766184Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation b66ac405-3a0a-4ced-a0a4-2cbd2d320290 · inbound

Lightning OPD: Efficient Post-Training for Large Reasoning Models with Offline On-Policy Distillation cites this paper.

Lightning OPD: Efficient Post-Training for Large Reasoning Models with Offline On-Policy Distillation ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:46:00.902942Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0162721a-59df-465d-87c7-96a8042457cc · inbound

BitRL: Reinforcement Learning with 1-bit Quantized Language Models for Resource-Constrained Edge Deployment cites this paper.

BitRL: Reinforcement Learning with 1-bit Quantized Language Models for Resource-Constrained Edge Deployment ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 20

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T21:46:42.470028Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a3d2df48-282d-404f-9325-17173f4a6ea6 · inbound

Listwise Policy Optimization: Group-based RLVR as Target-Projection on the LLM Response Simplex cites this paper.

Listwise Policy Optimization: Group-based RLVR as Target-Projection on the LLM Response Simplex ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-11T18:46:10.372171Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 8cdce20e-1b2a-48c3-8dca-d2c56cc51c9a · inbound

Listwise Policy Optimization: Group-based RLVR as Target-Projection on the LLM Response Simplex cites this paper.

Listwise Policy Optimization: Group-based RLVR as Target-Projection on the LLM Response Simplex ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-21T09:04:04.452971Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 68130dc2-706a-4799-bdea-c49286b38394 · inbound

The Cancellation Hypothesis in Critic-Free RL: From Outcome Rewards to Token Credits cites this paper.

The Cancellation Hypothesis in Critic-Free RL: From Outcome Rewards to Token Credits ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 10

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T08:01:29.028245Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation a798f6dd-ee22-49f2-83d9-6ee7af1dd054 · inbound

Internalizing Curriculum Judgment for LLM Reinforcement Fine-Tuning cites this paper.

Internalizing Curriculum Judgment for LLM Reinforcement Fine-Tuning ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-13T02:22:06.818446Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation ead685cd-698e-49f8-9719-4c5930606f63 · inbound

Self-Supervised On-Policy Distillation for Reasoning Language Models cites this paper.

Self-Supervised On-Policy Distillation for Reasoning Language Models ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 99

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:43:22.208303Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2f2f5fa2-f0a5-45b5-bd3f-952a6fc66c4d · inbound

Rethinking Muon Beyond Pretraining: Spectral Failures and High-Pass Remedies for VLA and RLVR cites this paper.

Rethinking Muon Beyond Pretraining: Spectral Failures and High-Pass Remedies for VLA and RLVR ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-05-20T07:18:07.233735Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation fb06da29-d7a0-4cb1-a23a-27508f0ed17d · inbound

Regulating Anatomy-Aware Rewards via Trajectory-Integral Feedback for Volumetric Computed Tomography Analysis cites this paper.

Regulating Anatomy-Aware Rewards via Trajectory-Integral Feedback for Volumetric Computed Tomography Analysis ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-21T08:09:51.805818Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 0a1d2f8a-47b6-474f-b7d9-c4d8ea84497a · inbound

Explicit Critic Guidance for Aligning Diffusion Models cites this paper.

Explicit Critic Guidance for Aligning Diffusion Models ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-06-29T18:23:50.787110Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 87373631-0bff-4bec-8c62-2e845eab17ec · inbound

Mechanistically Interpreting the Role of Sample Difficulty in RLVR for LLMs cites this paper.

Mechanistically Interpreting the Role of Sample Difficulty in RLVR for LLMs ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 20

Resolution: verified exact; arxiv_id, observed 2026-06-29T12:13:26.588012Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 64710dcb-d09d-4c00-99ab-0a71fbe94a6c · inbound

Trust Region On-Policy Distillation cites this paper.

Trust Region On-Policy Distillation ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 215

Resolution: verified exact; arxiv_id, observed 2026-07-01T20:56:13.678360Z

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Observation 3b77b3d6-6413-4afb-be35-9b8cd231d91f · inbound

Rethinking Groups in Critic-Free RLVR cites this paper.

Rethinking Groups in Critic-Free RLVR ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-07-03T17:58:47.902442Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 2618604b-2e5e-4b78-b562-3485ea2422f2 · inbound

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning cites this paper.

Modularized Reinforcement Learning on LLMs: From MDP Creation to Exploration and Learning ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 111

Resolution: verified exact; arxiv_id, observed 2026-07-04T08:09:40.663139Z

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No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.

Observation 5db4b711-2172-4457-8992-12fff20a36e2 · inbound

RSPO: Reward-Swap Policy Optimization for Multi-Turn LLM Agents cites this paper.

RSPO: Reward-Swap Policy Optimization for Multi-Turn LLM Agents ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 20

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Observation caa5c229-72ee-42f7-9314-b035d470078f · inbound

When RLVR Shrinks the Reasoning Boundary: Diagnosing Pass@k Inversion cites this paper.

When RLVR Shrinks the Reasoning Boundary: Diagnosing Pass@k Inversion ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 11

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Observation 807dbbc4-4eec-4054-bdb4-cf5469ab7aff · inbound

Lightning OPD 2.0: Mitigating Style Bias in Cross-Teacher On-Policy Distillation for Large Reasoning Models cites this paper.

Lightning OPD 2.0: Mitigating Style Bias in Cross-Teacher On-Policy Distillation for Large Reasoning Models ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-07-31T07:02:36.374494Z

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Observation 21b7eeaa-3378-4cf0-9f30-494b318e321e · inbound

CoRE: Consensus Rewards via Equilibrium for Test-Time Reinforcement Learning cites this paper.

CoRE: Consensus Rewards via Equilibrium for Test-Time Reinforcement Learning ReMax: A Simple, Effective, and Efficient Reinforcement Learning Method for Aligning Large Language Models

Reference 2022

Resolution: unresolved; no resolver link, observed 2026-08-11T19:31:40.843022Z

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