Paper Citation Record · LEDGER

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation

As of 18 August 2026, this Paper Citation Record lists 100 of 103 outbound references and 8 inbound Pith citation observations for arXiv:2412.15118.

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

pith.paper-citation-record.v1
2412.15118 v2

Coverage vector

measured 100 of 103 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:40:13.929186Z

measured 108 of 108 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T11:58:08.171009Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T10:58:14.255418Z

Reference resolution

100 of 103 outbound references displayed

verified exact3
verified fuzzy1
unresolved96
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation eb779ac7-74da-4e6f-ba6f-793873d6cf64 · outbound

This paper cites PaLM 2 Technical Report.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation PaLM 2 Technical Report

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 48e54348-a47b-4dd6-b543-c17e2b472023 · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.332953Z

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Observation 8ca6ce34-d9ce-4782-9db0-0def01dba5c0 · outbound

This paper cites Program Synthesis with Large Language Models.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Program Synthesis with Large Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.339021Z

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Observation 69a8cb3e-c54f-4e2a-95da-a94db4765208 · outbound

This paper cites A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation A Multitask, Multilingual, Multimodal Evaluation of ChatGPT on Reasoning, Hallucination, and Interactivity

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.345001Z

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Observation e0f71f89-34a9-421b-a6c3-dc25e02a9eac · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 5

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Observation d1bf37d6-071c-436c-9cd4-1285d0d56444 · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.358630Z

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Observation d21cccbd-1ebc-455f-812b-a82aefaae2b9 · outbound

This paper cites A Survey on Evaluation of Large Language Models.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation A Survey on Evaluation of Large Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.366864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 571876d5-c29b-4d38-b337-aaa84bc4bb75 · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.373671Z

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Observation 02db9a5c-1e71-4426-b6cc-829e4d8d7069 · outbound

This paper cites Humans or LLMs as the Judge? A Study on Judgement Biases.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Humans or LLMs as the Judge? A Study on Judgement Biases

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.379357Z

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Observation e0bd076b-a5d7-41c5-8003-40cd93367b9f · outbound

This paper cites AlphaMath Almost Zero: Process Supervision without Process.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation AlphaMath Almost Zero: Process Supervision without Process

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.386373Z

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Observation ee278aef-ea54-4115-a3b8-40d88eb7e7aa · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Evaluating Large Language Models Trained on Code

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.393373Z

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Observation 2487c80a-ee0d-45dd-8e23-1d60f9fa489a · outbound

This paper cites Teaching Large Language Models to Self-Debug.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Teaching Large Language Models to Self-Debug

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.399800Z

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Observation d68ad560-f7e8-49d3-ae7b-c9fb509d22fa · outbound

This paper cites AutoPRM: Automating Procedural Supervision for Multi-Step Reasoning via Controllable Question Decomposition.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation AutoPRM: Automating Procedural Supervision for Multi-Step Reasoning via Controllable Question Decomposition

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.416304Z

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Observation 3cf58c6e-759e-4c37-a097-3906855e84d5 · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.423677Z

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Observation 5ed50337-2d4b-475a-9901-97547d61ed10 · outbound

This paper cites Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Think you have Solved Question Answering? Try ARC, the AI2 Reasoning Challenge

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.430152Z

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Observation bf3b52c8-b1a3-40a6-8583-02113d899665 · outbound

This paper cites Training Verifiers to Solve Math Word Problems.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Training Verifiers to Solve Math Word Problems

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.437950Z

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Observation 2c0c0f92-8edd-4256-b486-10a6cba74533 · outbound

This paper cites Process Supervision-Guided Policy Optimization for Code Generation.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Process Supervision-Guided Policy Optimization for Code Generation

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.444151Z

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Observation 718b1a2a-829f-435d-a7e9-84b6e969e050 · outbound

This paper cites Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Fine-Tuning Pretrained Language Models: Weight Initializations, Data Orders, and Early Stopping

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.450996Z

Source-reported events for the cited work

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Observation 0cf9d67b-cf4d-494d-91c1-8369b2545292 · outbound

This paper cites The Llama 3 Herd of Models.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation The Llama 3 Herd of Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.457474Z

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Observation 5e511dbc-dea7-4cdc-964e-757d30254870 · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.463287Z

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Observation fbcea886-138e-4f7c-9c3f-fe928f0535ab · outbound

This paper cites Beam Search Strategies for Neural Machine Translation.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Beam Search Strategies for Neural Machine Translation

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.470380Z

Source-reported events for the cited work

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Observation 71639010-3403-4d9b-858d-4dcfa59b9da2 · outbound

This paper cites GPTScore: Evaluate as You Desire.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation GPTScore: Evaluate as You Desire

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.478494Z

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Observation d1c768ad-a2bd-421b-922f-c8c4cbc16db1 · outbound

This paper cites Dahl, Justin Gilmer, Christopher J.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Dahl, Justin Gilmer, Christopher J

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.484405Z

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Observation 224bbb40-72d6-4796-be00-2d3fc1946578 · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.490294Z

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Observation 26325a09-e1b4-4535-b8c7-5a4e6080b258 · outbound

This paper cites CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.496947Z

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Observation 413735c4-33a4-40d9-ad29-91cf9ef000c2 · outbound

This paper cites DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.503690Z

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Observation 3b1dc32b-1cc9-4a0f-89e9-510e79ceaaaa · outbound

This paper cites Advancing Process Verification for Large Language Models via Tree-Based Preference Learning.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Advancing Process Verification for Large Language Models via Tree-Based Preference Learning

Reference 27

Resolution: verified exact; local_arxiv, observed 2026-08-11T11:40:14.995566Z

Source-reported events for the cited work

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Observation f364168f-877b-4dee-9cbf-a984324bcd3a · outbound

This paper cites Semi-Supervised Reward Modeling via Iterative Self-Training.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Semi-Supervised Reward Modeling via Iterative Self-Training

Reference 28

Resolution: verified exact; local_arxiv, observed 2026-08-11T11:40:14.969016Z

Source-reported events for the cited work

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Observation 77366387-8d5f-4235-8154-b4b76b697fa8 · outbound

This paper cites Scaling Laws for Autoregressive Generative Modeling.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Scaling Laws for Autoregressive Generative Modeling

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.522298Z

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Observation 906d42df-e222-4e89-bba2-b79fd01457ed · outbound

This paper cites Hinton, Simon Osindero, and Yee Whye Teh.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Hinton, Simon Osindero, and Yee Whye Teh

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.528702Z

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Observation 4613e2ad-60d2-4bc3-bcc1-039481cc42c9 · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 31

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Observation 62ffa837-8c38-43c9-b7f3-bfbaf2c2ce2f · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.541064Z

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Observation d4ca5e5d-aad4-4125-adf2-1382a9ae72fc · outbound

This paper cites Are LLM-based Evaluators Confusing NLG Quality Criteria?.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Are LLM-based Evaluators Confusing NLG Quality Criteria?

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.547528Z

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Observation d5f4e840-29ec-4bb9-8cc5-6c59f15ee07a · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Large Language Models Cannot Self-Correct Reasoning Yet

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.553093Z

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Observation 6c8edc09-6616-4806-9ef9-c0e2b5273061 · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Qwen2.5-Coder Technical Report

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.559229Z

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Observation bea1843f-9860-4e6e-bbea-7067cbe75c6c · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation GPT-4o System Card

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.566559Z

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Observation 013e91a3-d384-4d50-8392-cad253850189 · outbound

This paper cites LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code

Reference 37

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Observation 1c8c8569-b99d-4c4a-8b5e-8f17464f976d · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Mistral 7B

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.579447Z

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Observation 6185c839-4d9e-40cb-b798-ea7dcb445a4a · outbound

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

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Enhancing LLM Reasoning with Reward-guided Tree Search

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.585941Z

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Observation ee75d066-34ed-4619-ba8c-90d85fa80f1d · outbound

This paper cites A Survey on Large Language Models for Code Generation.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation A Survey on Large Language Models for Code Generation

Reference 40

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Observation 7fd0cef1-7967-4e70-b4d2-e75dd1d7d11b · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Learning Planning-based Reasoning by Trajectories Collection and Process Reward Synthesizing

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.597847Z

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Observation a4031fc0-eddf-4762-b4a3-236bd58844fd · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation SWE-bench: Can Language Models Resolve Real-World GitHub Issues?

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.603785Z

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Observation 393e36fc-0f3a-42fd-a4f8-558e0697a9ec · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Scaling Laws for Neural Language Models

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.609436Z

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Observation ac1f2851-cec7-47fc-b596-79d03e25d699 · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 44

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Observation 2e669c07-0139-44e9-8c45-7f9f8c7a26cc · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 45

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Observation 07974324-4987-4663-a2bd-1bdd78ef541c · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 46

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Observation 3cde1b08-41f2-4dee-9ca0-237479debd84 · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 47

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation An Open Source Data Contamination Report for Large Language Models

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.645069Z

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Observation b6427d9d-7f28-4019-b73f-21c5aa7f21b0 · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Let's Verify Step by Step

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.651621Z

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Observation c8b105cd-79aa-482b-81db-f3865c31ebf7 · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Meta Semantic Template for Evaluation of Large Language Models

Reference 50

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Observation bf101bc8-f64e-4684-b1b5-bac166598201 · outbound

This paper cites Improve Mathematical Reasoning in Language Models by Automated Process Supervision.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Improve Mathematical Reasoning in Language Models by Automated Process Supervision

Reference 51

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Observation 63ea4412-c884-4f80-b341-8e80de917850 · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Let's reward step by step: Step-Level reward model as the Navigators for Reasoning

Reference 52

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Observation 2058e9b4-805b-45fe-90bc-afaf688edf9b · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation On Leakage of Code Generation Evaluation Datasets

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.674987Z

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Observation 4af0652d-564d-40b5-b3d6-3f917a5a24c6 · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 54

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation GPT-4 Technical Report

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.685597Z

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Observation e6209555-9d88-4aea-915b-8a9ec2cacd6c · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 56

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Observation 08237f47-4d3b-4546-b0d3-75185af396ce · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 57

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Instruction Tuning with GPT-4

Reference 58

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Observation 5580dfb0-741e-4c89-9fe9-8e88a02e9f5c · outbound

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Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.707344Z

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Observation 2bd6778b-26b4-4a5b-8dd4-f8ae8b2183dc · outbound

This paper cites O1 Replication Journey: A Strategic Progress Report -- Part 1.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation O1 Replication Journey: A Strategic Progress Report -- Part 1

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.712702Z

Source-reported events for the cited work

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Observation 14ca6ecd-a7e0-4276-b2b8-deeb8e6d1ae2 · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 61

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Observation b1929ca5-01e2-4bd6-8e38-807a34bc61ba · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 62

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.724209Z

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Observation a850b654-297f-4255-a6ed-2c197fdd104b · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.730809Z

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Observation ac13238f-0f06-4570-9d7b-daa90fe4f159 · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.736045Z

Source-reported events for the cited work

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Observation c18b0ef1-d468-4300-b5da-820f8aeabcdc · outbound

This paper cites Quantifying Contamination in Evaluating Code Generation Capabilities of Language Models.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Quantifying Contamination in Evaluating Code Generation Capabilities of Language Models

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.741946Z

Source-reported events for the cited work

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Observation 8bee9f43-dcec-4be2-8492-3dbce3ee2990 · outbound

This paper cites NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each Benchmark.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation NLP Evaluation in trouble: On the Need to Measure LLM Data Contamination for each Benchmark

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.747358Z

Source-reported events for the cited work

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Observation 63aa9c1b-7836-47ec-b3b1-6a2b0d540ee0 · outbound

This paper cites Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Rewarding Progress: Scaling Automated Process Verifiers for LLM Reasoning

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.752799Z

Source-reported events for the cited work

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Observation fbe26c91-494d-4cd4-ab6f-79e3f0cb32c2 · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 68

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.758402Z

Source-reported events for the cited work

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Observation bfe8fd6e-b055-490b-bfc0-6fe771d47094 · outbound

This paper cites Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Scaling LLM Test-Time Compute Optimally can be More Effective than Scaling Model Parameters

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.763961Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b0862f90-c68e-4f08-b481-a138e64786dc · outbound

This paper cites On the Self-Verification Limitations of Large Language Models on Reasoning and Planning Tasks.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation On the Self-Verification Limitations of Large Language Models on Reasoning and Planning Tasks

Reference 70

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.768870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a23c88d4-eddc-4a1c-9635-9ac03d8cde51 · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 71

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:40:15.535541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 264fa6b7-655f-4d66-9682-926a970e593a · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 72

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.779711Z

Source-reported events for the cited work

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Observation 4ad801e4-71e0-44e9-bd03-b0ea41956fb3 · outbound

This paper cites Judging the Judges: Evaluating Alignment and Vulnerabilities in LLMs-as-Judges.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Judging the Judges: Evaluating Alignment and Vulnerabilities in LLMs-as-Judges

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.784558Z

Source-reported events for the cited work

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Observation ec22dddc-6227-43ce-bedc-20b547d0a87a · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation LLaMA: Open and Efficient Foundation Language Models

Reference 74

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.790258Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db5436e3-6fe1-409b-bcad-8ff00ed1b358 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 75

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.795348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f54e275-f0f6-4c91-9d4b-c57c7f884569 · outbound

This paper cites O'Reilly Media, Inc.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation O'Reilly Media, Inc

Reference 76

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T11:40:15.506648Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 32697a24-177a-4297-8ae0-ef41e45f7d0a · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 77

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:40:15.490111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 71e3acb8-cfef-40a7-8530-a8ade31f8ff5 · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 78

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.810982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38bb94fe-32ae-46db-b1d3-74ec00e204d9 · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 79

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:40:15.463141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ad2f1259-4227-4913-9767-f5930e584838 · outbound

This paper cites LiteSearch: Efficacious Tree Search for LLM.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation LiteSearch: Efficacious Tree Search for LLM

Reference 80

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.821121Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fb6e278f-ed16-422d-98d7-ca0b3dd8de81 · outbound

This paper cites Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Survey on Factuality in Large Language Models: Knowledge, Retrieval and Domain-Specificity

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.826193Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a40f116-9eec-4c21-85f3-b61566470e12 · outbound

This paper cites OpenR: An Open Source Framework for Advanced Reasoning with Large Language Models.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation OpenR: An Open Source Framework for Advanced Reasoning with Large Language Models

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.831745Z

Source-reported events for the cited work

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Observation c75ed5a7-93c1-4fbb-af81-d44735a28339 · outbound

This paper cites Large Language Models are not Fair Evaluators.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Large Language Models are not Fair Evaluators

Reference 83

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.837438Z

Source-reported events for the cited work

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Observation 159e4030-edab-4a16-9265-e72cdff72edb · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 84

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:40:15.445894Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f6a00e54-171b-4f3e-81b9-cd8531abd3df · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 85

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:40:15.427496Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation bfede6a1-675d-4638-943a-23621287a16e · outbound

This paper cites PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization

Reference 86

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.855139Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 438d267f-5880-46e6-9d58-8d3fd5e5e99a · outbound

This paper cites Self-Instruct: Aligning Language Models with Self-Generated Instructions.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Self-Instruct: Aligning Language Models with Self-Generated Instructions

Reference 87

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.860596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8801108c-3171-4f01-ad1f-724db8663534 · outbound

This paper cites Multi-step Problem Solving Through a Verifier: An Empirical Analysis on Model-induced Process Supervision.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Multi-step Problem Solving Through a Verifier: An Empirical Analysis on Model-induced Process Supervision

Reference 88

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.865853Z

Source-reported events for the cited work

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Observation b6765415-6822-46f7-942d-58f02dcf96c0 · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 89

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.870917Z

Source-reported events for the cited work

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Observation 1c7dc39a-38f4-4129-8af0-d0d2aaecc3e3 · outbound

This paper cites CodeShell Technical Report.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation CodeShell Technical Report

Reference 90

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.876078Z

Source-reported events for the cited work

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Observation 51193056-39d4-4b0c-8ed2-3b0bb6ff4a87 · outbound

This paper cites Watch Every Step! LLM Agent Learning via Iterative Step-Level Process Refinement.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Watch Every Step! LLM Agent Learning via Iterative Step-Level Process Refinement

Reference 91

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.881355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8424e32a-a3de-4ffa-b582-5b09185da12c · outbound

This paper cites GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-distribution Generalization Perspective.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-distribution Generalization Perspective

Reference 92

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.886611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 46f96e20-fa5d-40a0-b1ad-bcf95afe31bd · outbound

This paper cites Supervised Knowledge Makes Large Language Models Better In-context Learners.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Supervised Knowledge Makes Large Language Models Better In-context Learners

Reference 93

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.891905Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 409370a7-37e9-4592-8142-4f04cb7d625f · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 94

Resolution: unresolved; raw_fallback, observed 2026-08-11T11:40:15.399530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 168a38d8-d0e8-4935-9cf4-2928fc98de1f · outbound

This paper cites KIEval: A Knowledge-grounded Interactive Evaluation Framework for Large Language Models.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation KIEval: A Knowledge-grounded Interactive Evaluation Framework for Large Language Models

Reference 95

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.902661Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7dca7866-e9b6-499c-960e-481489b1c060 · outbound

This paper cites FreeEval: A Modular Framework for Trustworthy and Efficient Evaluation of Large Language Models.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation FreeEval: A Modular Framework for Trustworthy and Efficient Evaluation of Large Language Models

Reference 96

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.907632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 44145f61-6d57-4e46-b63e-bd490181b2cc · outbound

This paper cites ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation ReST-MCTS*: LLM Self-Training via Process Reward Guided Tree Search

Reference 97

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.912864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4d04ced9-301d-491b-b09b-03dd2e75241a · outbound

This paper cites Self-Edit: Fault-Aware Code Editor for Code Generation.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Self-Edit: Fault-Aware Code Editor for Code Generation

Reference 98

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.918207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eea1c3be-2348-4fce-8645-6c5714fd2147 · outbound

This paper cites an unresolved cited work.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation Unresolved cited work

Reference 99

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.923794Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d0d6d59-2602-4195-9925-7553791389f7 · outbound

This paper cites LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models.

Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation LlamaFactory: Unified Efficient Fine-Tuning of 100+ Language Models

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-11T11:40:13.929186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 09d531f7-c4fd-4a71-8e9c-f5a60d88606c · inbound

Tree-of-Code: A Tree-Structured Exploring Framework for End-to-End Code Generation and Execution in Complex Task Handling cites this paper.

Tree-of-Code: A Tree-Structured Exploring Framework for End-to-End Code Generation and Execution in Complex Task Handling Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-11T11:58:08.171009Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 203cd53b-02d3-43fe-a313-1771f3ae7f2b · 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 Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation

Reference 165

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:36:24.180661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d1464911-8e0c-4a5c-9e45-9069c5ea5cba · inbound

RewardAnything: Generalizable Principle-Following Reward Models cites this paper.

RewardAnything: Generalizable Principle-Following Reward Models Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-07T11:04:06.882676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52545019-4836-4976-b621-651dc3176642 · inbound

Uncertainty-aware Reward Design Process cites this paper.

Uncertainty-aware Reward Design Process Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-06T20:39:15.005796Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17a017c2-4a37-4946-8c7f-74c9554f0182 · inbound

Let's Revise Step-by-Step: A Unified Local Search Framework for Code Generation with LLMs cites this paper.

Let's Revise Step-by-Step: A Unified Local Search Framework for Code Generation with LLMs Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-05T22:09:46.486332Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 17a3fe2c-b1a3-4d2b-b814-9c5777247b80 · inbound

PaT: Planning-after-Trial for Efficient Test-Time Code Generation cites this paper.

PaT: Planning-after-Trial for Efficient Test-Time Code Generation Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation

Reference 26

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T02:45:59.120557Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 34ea2427-17f8-4f5d-beef-f730b276871f · inbound

PYTHALAB-MERA: Validation-Grounded Memory, Retrieval, and Acceptance Control for Frozen-LLM Coding Agents cites this paper.

PYTHALAB-MERA: Validation-Grounded Memory, Retrieval, and Acceptance Control for Frozen-LLM Coding Agents Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation

Reference 48

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:21:26.085532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 76e3a7e2-e4c0-4404-9ab0-152fada9cb12 · inbound

Code as Agent Harness cites this paper.

Code as Agent Harness Reasoning Through Execution: Unifying Process and Outcome Rewards for Code Generation

Reference 97

Resolution: verified exact; arxiv_id, observed 2026-05-20T10:58:14.257707Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.