Paper Citation Record · LEDGER

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization

As of 9 August 2026, this Paper Citation Record lists 35 of 35 outbound references and 2 inbound Pith citation observations for arXiv:2505.18830.

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

pith.paper-citation-record.v1
2505.18830 v1

Coverage vector

measured 35 of 35 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:29:34.013794Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T09:34:06.517190Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-11T15:16:09.090199Z

Reference resolution

35 of 35 outbound references displayed

verified exact1
verified fuzzy7
unresolved26
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 1c2ffe78-a13b-4ec9-8192-4f7d15c71d18 · outbound

This paper cites Gpg: A simple and strong reinforcement learning baseline for model reasoning.arXiv preprint arXiv:2504.02546, 2025.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Gpg: A simple and strong reinforcement learning baseline for model reasoning.arXiv preprint arXiv:2504.02546, 2025

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:30.082862Z

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Unavailable: canonical work link unavailable.

Observation 3519a9e7-04f0-4dbb-8464-61e670ba6ace · outbound

This paper cites DARE the Extreme: Revisiting Delta-Parameter Pruning For Fine-Tuned Models.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization DARE the Extreme: Revisiting Delta-Parameter Pruning For Fine-Tuned Models

Reference 2

Resolution: verified exact; local_arxiv, observed 2026-08-07T14:29:34.477945Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b8da91cd-c47c-4176-8984-193b2cd7c071 · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:30.352756Z

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Observation 0086d934-0735-4c00-b015-e426cf4b1793 · outbound

This paper cites OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:30.472429Z

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Observation ac04d9fc-c2c3-43dd-8890-51ecedb29804 · outbound

This paper cites The local elasticity of neural networks.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization The local elasticity of neural networks

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:29:35.731705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4e9a462d-48e0-493d-a2e0-c32b91e59503 · outbound

This paper cites Measuring mathematical problem solving with the math dataset.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Measuring mathematical problem solving with the math dataset

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:30.787987Z

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Observation 01ee2673-2467-4663-a4dc-fe0a0a5ef0a9 · outbound

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

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Open-Reasoner-Zero: An Open Source Approach to Scaling Up Reinforcement Learning on the Base Model

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:30.979686Z

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Observation e5e4e96a-22cc-4bcf-a91a-88ad472cf7c5 · outbound

This paper cites OpenAI o1 System Card.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization OpenAI o1 System Card

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:31.111041Z

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Observation 2e95c004-02d1-453c-956a-8e17c1eb7a31 · outbound

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

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Search-R1: Training LLMs to Reason and Leverage Search Engines with Reinforcement Learning

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:31.259139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0213d9c1-098d-47b5-98e7-bc3263b303e9 · outbound

This paper cites Med-r1: Reinforce- ment learning for generalizable medical reasoning in vision-language models.arXiv preprint arXiv:2503.13939, 2025.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Med-r1: Reinforce- ment learning for generalizable medical reasoning in vision-language models.arXiv preprint arXiv:2503.13939, 2025

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:31.370676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 287758ef-d131-493f-a2a3-6fab4b88f346 · outbound

This paper cites Solving quantitative reasoning problems with language models.Advances in Neural Information Processing Systems, 35:3843–3857, 2022.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Solving quantitative reasoning problems with language models.Advances in Neural Information Processing Systems, 35:3843–3857, 2022

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:31.497301Z

Source-reported events for the cited work

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Observation 9138a9b8-c697-454e-9c8b-b2c04ae9b2f8 · outbound

This paper cites Understanding R1-Zero-Like Training: A Critical Perspective.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Understanding R1-Zero-Like Training: A Critical Perspective

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:31.672136Z

Source-reported events for the cited work

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Observation 4bbda4f8-5219-4a63-b4d3-aca75d7097e0 · outbound

This paper cites Deepscaler: Surpassing o1-preview with a 1.5b model by scaling rl, 2025.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Deepscaler: Surpassing o1-preview with a 1.5b model by scaling rl, 2025

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:31.844838Z

Source-reported events for the cited work

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Observation 65cf08cb-4b81-423b-9bfe-765f73129ae8 · outbound

This paper cites Neural collapse with unconstrained features.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Neural collapse with unconstrained features

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:29:35.585539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation cc9af7d2-8533-41df-8f1b-6f9a67183a9e · outbound

This paper cites Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Smaug: Fixing Failure Modes of Preference Optimisation with DPO-Positive

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:32.198096Z

Source-reported events for the cited work

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Observation fd6b3d69-c9a3-4268-8dc1-340694b26bfb · outbound

This paper cites Direct preference optimization: Your language model is secretly a reward model.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Direct preference optimization: Your language model is secretly a reward model

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:32.334464Z

Source-reported events for the cited work

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Observation d3f472fa-05a6-4984-b680-13d8fa5b52de · outbound

This paper cites Unintentional Unalignment: Likelihood Displacement in Direct Preference Optimization.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Unintentional Unalignment: Likelihood Displacement in Direct Preference Optimization

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:32.444781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cb0aa861-d8ce-4d6a-9d29-a536550589d8 · outbound

This paper cites Learning Dynamics of LLM Finetuning.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Learning Dynamics of LLM Finetuning

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:32.572317Z

Source-reported events for the cited work

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Observation 41608882-f242-4ed3-8191-4bc586c69a70 · outbound

This paper cites Proximal Policy Optimization Algorithms.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Proximal Policy Optimization Algorithms

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:32.710722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 726ede61-1ee1-403e-9235-575fa2c83438 · outbound

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

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:32.815490Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01b333f3-1f0b-4378-a7d7-4d48e3286691 · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Gemini: A Family of Highly Capable Multimodal Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:32.921726Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96dff3bd-5d64-4f4f-ae3c-5372b0de278a · outbound

This paper cites Aime problem set 1983-2024, 2023.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Aime problem set 1983-2024, 2023

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:29:35.509164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 21575429-1287-40a5-b8cd-f7afa7856141 · outbound

This paper cites Qwen2.5 Technical Report.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Qwen2.5 Technical Report

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:33.073364Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a15f090f-5325-4091-b01e-7fe9210c3d57 · outbound

This paper cites Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:33.120361Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bd1349c0-d83a-4598-8710-ddbb685d6d35 · outbound

This paper cites Breaking the Softmax Bottleneck: A High-Rank RNN Language Model.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Breaking the Softmax Bottleneck: A High-Rank RNN Language Model

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:33.191566Z

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Observation 86e8509a-9d1f-4541-8271-238cb2c324a4 · outbound

This paper cites MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:33.267870Z

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Observation 1e7a4dd1-a25f-4783-b71d-bac8905ba860 · outbound

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

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization DAPO: An Open-Source LLM Reinforcement Learning System at Scale

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:33.323315Z

Source-reported events for the cited work

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Observation 5bab72b9-5519-4cfb-8f12-b78c64860908 · outbound

This paper cites Advancing LLM Reasoning Generalists with Preference Trees.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Advancing LLM Reasoning Generalists with Preference Trees

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:33.431718Z

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Observation b04807af-9df9-4bc3-b30c-5558edf2ef4f · outbound

This paper cites SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization SimpleRL-Zoo: Investigating and Taming Zero Reinforcement Learning for Open Base Models in the Wild

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:33.492988Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4177ec77-2d36-4819-af22-815479f91d08 · outbound

This paper cites Implicit Geometry of Next-token Prediction: From Language Sparsity Patterns to Model Representations.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Implicit Geometry of Next-token Prediction: From Language Sparsity Patterns to Model Representations

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-07T14:29:33.608339Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93de0474-6ead-4896-9f95-87061801dad4 · outbound

This paper cites one commercially available ten-button lock may be opened by pressing – in any order – the correct five buttons.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization one commercially available ten-button lock may be opened by pressing – in any order – the correct five buttons

Reference 31

Resolution: malformed identifier; raw_fallback, observed 2026-08-07T14:29:35.313069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 37e0f6f9-5bc9-40c9-95f9-8c882721387e · outbound

This paper cites From the given graph, we can observe the following: - The roots off(x)are atx= 1 andx= 3.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization From the given graph, we can observe the following: - The roots off(x)are atx= 1 andx= 3

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:29:35.094259Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1ad0abfb-49ad-4c55-80ac-4b4a33f33c88 · outbound

This paper cites Therefore: - The roots of g(x)are also atx= 1 andx= 3.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization Therefore: - The roots of g(x)are also atx= 1 andx= 3

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:29:34.956361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 7ba4801a-f4b9-485c-8328-5cb5b74f5928 · outbound

This paper cites This simplifies to: f(x) = 0 The roots off(x)are atx= 1 andx= 3.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization This simplifies to: f(x) = 0 The roots off(x)are atx= 1 andx= 3

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:29:34.870775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d34fc82a-47eb-4b63-883c-158d98591680 · outbound

This paper cites This implies thatf(x)is an even function, and its graph is symmetric about the y-axis.

On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization This implies thatf(x)is an even function, and its graph is symmetric about the y-axis

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T14:29:34.738641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

Observation 151aac32-085e-47ea-a121-e760e2719af9 · inbound

Beyond the Sampled Token: Preserving Candidate Support in RLVR cites this paper.

Beyond the Sampled Token: Preserving Candidate Support in RLVR On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T09:34:06.517190Z

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Observation 89a73c6b-0b37-423f-a8fd-f01398c0874b · inbound

Odysseus: Scaling VLMs to 100+ Turn Decision-Making in Games via Reinforcement Learning cites this paper.

Odysseus: Scaling VLMs to 100+ Turn Decision-Making in Games via Reinforcement Learning On the Effect of Negative Gradient in Group Relative Deep Reinforcement Optimization

Reference 78

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:16:09.093200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.