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Paper Citation Record · LEDGER

LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 35 inbound Pith citation observations for arXiv:2504.14655.

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

pith.paper-citation-record.v1
2504.14655 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 35 of 35 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00

measured 35 of 35 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T14:00:53.161982Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T18:30:01.590053Z

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

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Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation cbab64a0-80cd-4115-98ff-ef427404d89a · inbound

When More is Less: Understanding Chain-of-Thought Length in LLMs cites this paper.

When More is Less: Understanding Chain-of-Thought Length in LLMs LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 44

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no resolver link, observed 2026-08-08T13:23:22.145829Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:23:22.145829Z digest=sha256:ce818fcd91056432c95273312d3dedfe251fb1127625c936171e1022e07c2467

Observation e039299b-129a-4617-983d-d56ca6c284bd · inbound

Skywork Open Reasoner 1 Technical Report cites this paper.

Skywork Open Reasoner 1 Technical Report LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 30

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arxiv_id, observed 2026-05-17T04:26:47.355380Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-17T04:26:47.283983Z digest=sha256:e070afa8906ad681f7793731701737a912553e7aa954ae367d9261f3f3facbdf

Observation c3ecf66b-b835-4348-9251-46c8cdb2961b · inbound

LLM Performance for Code Generation on Noisy Tasks cites this paper.

LLM Performance for Code Generation on Noisy Tasks LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 3

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no resolver link, observed 2026-08-07T12:45:40.247629Z

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source=pdf_text observed=2026-08-07T12:45:40.247629Z digest=sha256:eb4b9dfd10fcd16dbcbb6c926ba22c22bd639c7f3275da03292ac7f02d43ac26

Observation 88adc4bf-2f71-4e37-9529-14dff9aec9bb · inbound

LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in Competitive Programming? cites this paper.

LiveCodeBench Pro: How Do Olympiad Medalists Judge LLMs in Competitive Programming? LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 54

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T01:08:01.421727Z digest=sha256:f676ac0968183b440aa97f8296b8c97d628324895b36a7f3d0d528b65c94b12e

Observation 6b5cf1a2-b129-471d-9d83-79b48f9e7118 · inbound

Thunder-LLM: Efficiently Adapting LLMs to Korean with Minimal Resources cites this paper.

Thunder-LLM: Efficiently Adapting LLMs to Korean with Minimal Resources LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 76

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no resolver link, observed 2026-08-06T23:58:09.855676Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:58:09.855676Z digest=sha256:fa4d9792d849a47b288b6051443aa0ba1944da175668fab1e47992c0346464f9

Observation b8b0e9da-da06-47ad-8c4d-09724995ea1a · inbound

Teaching LLM to Reason: Reinforcement Learning from Algorithmic Problems without Code cites this paper.

Teaching LLM to Reason: Reinforcement Learning from Algorithmic Problems without Code LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 49

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no resolver link, observed 2026-08-06T18:43:59.848050Z

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T18:43:59.848050Z digest=sha256:c05a7135f4c366bc23a88f5431b7dbc594336f4e87297bd189eb3cced07bd372

Observation 1a497670-7b41-4cbb-b7e6-25af520195d5 · inbound

Small Edits, Big Consequences: Telling Good from Bad Robustness in Large Language Models cites this paper.

Small Edits, Big Consequences: Telling Good from Bad Robustness in Large Language Models LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 1

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T17:26:57.798530Z digest=sha256:4236d4e71d5b4f01507129661b82dfdb80fece52751257884328260f59fb7622

Observation bd8c166a-4143-41dc-9d89-038eee7ac710 · inbound

Re:Form -- Reducing Human Annotations in Scalable Formal Software Verification with RL in LLMs: A Preliminary Study on Dafny cites this paper.

Re:Form -- Reducing Human Annotations in Scalable Formal Software Verification with RL in LLMs: A Preliminary Study on Dafny LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 88

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source=arxiv_source observed=2026-08-06T15:20:17.686438Z digest=sha256:db4553c599ea931a08c8bddabf3a7a561c970cad4fda0a995fea7aaf35753176

Observation a669a212-d3d2-46c4-8b50-39da3cbb3553 · inbound

Can One Domain Help Others? A Data-Centric Study on Multi-Domain Reasoning via Reinforcement Learning cites this paper.

Can One Domain Help Others? A Data-Centric Study on Multi-Domain Reasoning via Reinforcement Learning LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 36

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no resolver link, observed 2026-08-06T14:53:04.611175Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T14:53:04.611175Z digest=sha256:812370fb96e002fc4001b10c39957b8d73d448c3756bb004053874a0476378ba

Observation 477d0844-47a5-426b-b416-27b06eee984e · inbound

Multi-LLM Orchestration for High-Quality Code Generation: Exploiting Complementary Model Strengths cites this paper.

Multi-LLM Orchestration for High-Quality Code Generation: Exploiting Complementary Model Strengths LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 68

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arxiv_id, observed 2026-05-18T10:22:33.298510Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-18T10:22:09.037783Z digest=sha256:26a1ecf8e43a38ebf34af7fa5222816724da2927c6fd976909a2d5562c893219

Observation c5509687-8d24-4de0-8b8a-917d97791d98 · inbound

CodeRL+: Improving Code Generation via Reinforcement with Execution Semantics Alignment cites this paper.

CodeRL+: Improving Code Generation via Reinforcement with Execution Semantics Alignment LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 27

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arxiv_id, observed 2026-05-18T05:20:54.593415Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-18T05:16:28.008746Z digest=sha256:72fa9eadccc805b7b947b6f61fbcb616d647da011266b4dbf980f8f15cdd8478

Observation 9b42878a-468e-41b8-96ca-7a3cfc5e8e58 · inbound

InfoSynth: Information-Guided Benchmark Synthesis for LLMs cites this paper.

InfoSynth: Information-Guided Benchmark Synthesis for LLMs LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 38

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-03T13:06:59.145164Z digest=sha256:63dd3d3d9ae169802e6581ff9e866596f56eadbed8cee90f06cf3b5d82df5de8

Observation c3a0e1d5-75e5-4c76-afdd-9629eaaf4912 · inbound

Think Anywhere in Code Generation cites this paper.

Think Anywhere in Code Generation LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 24

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arxiv_id, observed 2026-05-13T23:18:25.538454Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-13T23:16:42.782431Z digest=sha256:595abb44615df5367b162f82aad3513f0b9402f057a06b45333020b6c7bb1f53

Observation d0ec1a28-94b9-4385-aa21-1d56f7429326 · inbound

ACES: Who Tests the Tests? Leave-One-Out AUC Consistency for Code Generation cites this paper.

ACES: Who Tests the Tests? Leave-One-Out AUC Consistency for Code Generation LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 17

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no resolver link, observed 2026-07-13T12:00:02.401705Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T12:00:02.401705Z digest=sha256:83ffb9e9458f4c9652bb6143780c3b2525ff84ca9fba0935ac7b08595c21a330

Observation 7d1c0462-b7d0-4a3f-9062-d1db139bbf3d · inbound

ACES: Who Tests the Tests? Leave-One-Out AUC Consistency for Code Generation cites this paper.

ACES: Who Tests the Tests? Leave-One-Out AUC Consistency for Code Generation LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 17

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no resolver link, observed 2026-07-14T19:54:08.600196Z

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T19:54:08.600196Z digest=sha256:b599671f7419ecefab91ef911d5673b2cb942bc826c8da9f467314af6265ee9e

Observation 141223fe-3244-469e-968b-53ab39482ae0 · inbound

QiMeng-PRepair: Precise Code Repair via Edit-Aware Reward Optimization cites this paper.

QiMeng-PRepair: Precise Code Repair via Edit-Aware Reward Optimization LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 4

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arxiv_id, observed 2026-05-11T00:10:50.836308Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-10T18:41:12.750879Z digest=sha256:dd6252737a9c5cd7750ccb49ad57dfcf8b9b33c6cb9c6469f932d9f3ad2e4fc7

Observation 1873c522-6a14-4526-b96f-1d4322fa7e86 · inbound

CodeSpecBench: Benchmarking LLMs for Executable Behavioral Specification Generation cites this paper.

CodeSpecBench: Benchmarking LLMs for Executable Behavioral Specification Generation LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 37

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arxiv_id, observed 2026-05-11T11:26:03.588091Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-05-10T14:54:51.051959Z digest=sha256:a881efc4b84035c8c53f7854b6563f69c5f2fdbcbf320f469b30cf734c027032

Observation e71600fe-315f-40f2-80bb-15e9c5bf4784 · inbound

Steerable Instruction Following Coding Data Synthesis with Actor-Parametric Schema Co-Evolution cites this paper.

Steerable Instruction Following Coding Data Synthesis with Actor-Parametric Schema Co-Evolution LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 28

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arxiv_id, observed 2026-05-15T18:01:25.334520Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-15T18:00:39.404711Z digest=sha256:2539ab2c47ca2b760719d2e8aab592fb8cfeb0f9fb2e2dae7dfed296fc72a8da

Observation b622e4c6-f455-4a15-b8b5-4a04ef8f3039 · inbound

Do Prompt-Elicited Trajectories Reflect Training-Time Reward Hacking? A Systematic Study on Monitoring Training-Time Reward Hacking in Code Generation cites this paper.

Do Prompt-Elicited Trajectories Reflect Training-Time Reward Hacking? A Systematic Study on Monitoring Training-Time Reward Hacking in Code Generation LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 13

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arxiv_id, observed 2026-05-11T21:11:10.331536Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-08T06:38:32.413172Z digest=sha256:19d823b5470fe69283c5dcefcd72d8285bc219f02fcee7e589b1a8a03792ea8e

Observation 11f3c5fd-13c7-4875-be25-a6711bf71dc1 · inbound

Do Prompt-Elicited Trajectories Reflect Training-Time Reward Hacking? A Systematic Study on Monitoring Training-Time Reward Hacking in Code Generation cites this paper.

Do Prompt-Elicited Trajectories Reflect Training-Time Reward Hacking? A Systematic Study on Monitoring Training-Time Reward Hacking in Code Generation LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 13

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arxiv_id, observed 2026-07-01T10:05:40.195801Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-07-01T09:56:48.019404Z digest=sha256:be6ff4fcd65510cbefa0bad5623609f3c9b30bf21984c1c4c7804b5ba77cfd37

Observation b24afdd9-471f-4e1d-bd83-03f676b31a0f · inbound

Do Prompt-Elicited Trajectories Reflect Training-Time Reward Hacking? A Systematic Study on Monitoring Training-Time Reward Hacking in Code Generation cites this paper.

Do Prompt-Elicited Trajectories Reflect Training-Time Reward Hacking? A Systematic Study on Monitoring Training-Time Reward Hacking in Code Generation LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 5

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no resolver link, observed 2026-08-04T05:25:41.152925Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:25:41.152925Z digest=sha256:c577abdde8e7123b1cebb868e45fd201ad33d26403638529790cc4bc7846556b

Observation 5b42439a-d642-41dd-93dc-5a5a62d2baab · inbound

Schedule-and-Calibrate: Utility-Guided Multi-Task Reinforcement Learning for Code LLMs cites this paper.

Schedule-and-Calibrate: Utility-Guided Multi-Task Reinforcement Learning for Code LLMs LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 24

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arxiv_id, observed 2026-05-11T20:26:10.412611Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-08T09:11:20.733960Z digest=sha256:5b14888ac70b331b09e9868da45c79423b86987b2764116b5178992bdd167efb

Observation fe0f54f0-85b2-46d0-b37e-68742d50efe2 · inbound

SOD: Step-wise On-policy Distillation for Small Language Model Agents cites this paper.

SOD: Step-wise On-policy Distillation for Small Language Model Agents LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 75

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arxiv_id, observed 2026-05-11T03:40:54.525214Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-11T02:25:59.056181Z digest=sha256:cb804c5aedcf6ed6f597adec0cb45c60e5c91b5b8207c93b3dd1529df1f9647d

Observation e3b58194-f65f-4788-a235-2c21bf6ce13f · inbound

SOD: Step-wise On-policy Distillation for Small Language Model Agents cites this paper.

SOD: Step-wise On-policy Distillation for Small Language Model Agents LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 75

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no resolver link, observed 2026-08-04T05:20:45.244544Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:20:45.244544Z digest=sha256:284be57020800b4dd8c61cd8cba636cb4444bef39a50aa92e01a60584243765c

Observation d2beaf0a-b1c1-4f47-89e7-c42a07dc93d6 · inbound

Learning from Failures: Correction-Oriented Policy Optimization with Verifiable Rewards cites this paper.

Learning from Failures: Correction-Oriented Policy Optimization with Verifiable Rewards LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 34

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arxiv_id, observed 2026-05-15T01:43:27.576125Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-15T01:41:31.631505Z digest=sha256:6020365b2ad566eacc809c40ef7c92adbf2223585322f61dc1359f6750d3a570

Observation 14231b6c-ba56-4479-b9c2-6c7635052711 · inbound

Enhancing the Code Reasoning Capabilities of LLMs via Consistency-based Reinforcement Learning cites this paper.

Enhancing the Code Reasoning Capabilities of LLMs via Consistency-based Reinforcement Learning LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 40

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arxiv_id, observed 2026-05-20T13:18:18.455978Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-20T13:13:51.081597Z digest=sha256:1e70989a2d54ab64873919152058ff66dc5cb0ba98a5cac99bc1017928f6cef1

Observation 17538fcb-026f-4dcf-b60e-c6ea31afe80a · inbound

Hybrid-LoRA: Bridging Full Fine-Tuning and Low-Rank Adaptation for Post-Training cites this paper.

Hybrid-LoRA: Bridging Full Fine-Tuning and Low-Rank Adaptation for Post-Training LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 9

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verified exact
arxiv_id, observed 2026-05-20T22:23:47.696918Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-05-20T22:22:50.299625Z digest=sha256:af2cdcebd7f896527cd044f5060e5b0cd1a484d53d2dc6932a1c96b1cbfaa14d

Observation bce36ece-1f7a-429c-a34c-0f0f7f459a10 · inbound

MONA: Muon Optimizer with Nesterov Acceleration for Scalable Language Model Training cites this paper.

MONA: Muon Optimizer with Nesterov Acceleration for Scalable Language Model Training LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 51

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arxiv_id, observed 2026-06-29T19:23:54.151382Z

Source-reported events for the cited work

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

source=arxiv_source observed=2026-06-29T19:15:49.229099Z digest=sha256:6e5f6fb4cc78080fb993b382466e6ad23bbb88f5f311d16524ba6a297fb010a1

Observation 4529a888-af0d-41e7-bd28-683a40258d37 · inbound

Transferability for General Reasoning: An Automated Curriculum for Multi-Domain RLVR cites this paper.

Transferability for General Reasoning: An Automated Curriculum for Multi-Domain RLVR LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 57

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arxiv_id, observed 2026-07-04T18:30:01.591682Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-06-25T22:47:09.330723Z digest=sha256:71e411c98d2a178cc8b651aae8002079baf2512fd63c0ee970e21bdfaf0a1a45

Observation 2f1882cb-9cb1-43b4-8c28-dfabe97aa7e3 · inbound

Transferability for General Reasoning: An Automated Curriculum for Multi-Domain RLVR cites this paper.

Transferability for General Reasoning: An Automated Curriculum for Multi-Domain RLVR LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 57

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arxiv_id, observed 2026-06-30T12:54:40.439898Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-06-30T09:55:19.804589Z digest=sha256:2450b2ec5ac7be8b31bc728d3b0210a6dc69af1846384d48918479869df01f66

Observation 0577f2a4-6adc-4ad4-956e-dff38ca3f0eb · inbound

Do Machines Struggle Where Humans Do? LLM and Human Comprehension of Obfuscated Code cites this paper.

Do Machines Struggle Where Humans Do? LLM and Human Comprehension of Obfuscated Code LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 9

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arxiv_id, observed 2026-07-01T11:35:42.800992Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-07-01T04:20:58.193962Z digest=sha256:2986a9c6cb37eb845432f38905d505f4836eb6ccd1ef7de9399d13d833b1b551

Observation a84ff77f-299f-4d58-9c6d-e18488256e0c · inbound

Diversifying to Verify: When Task-Equivalent Programs Differ in Verifiability cites this paper.

Diversifying to Verify: When Task-Equivalent Programs Differ in Verifiability LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 27

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no resolver link, observed 2026-07-13T03:34:35.116630Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-13T03:34:35.116630Z digest=sha256:defc643400c5095fdc5905f6f2cfeb3e64a11c92450493979c2412cf9add5ac7

Observation f3163d5b-85a4-4540-bacb-13911226eac0 · inbound

Loop the Loopies! cites this paper.

Loop the Loopies! LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 78

Resolution
unresolved
no resolver link, observed 2026-08-01T21:34:28.035103Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T21:34:28.035103Z digest=sha256:340d0b3a01cae0d9b3932212ccd46654d267b40eb8b9526b60ce207da97fafe3

Observation 63972755-8e1c-4bd2-b8cb-66c9de8a73bd · inbound

Teaching LLMs to Self-Evolve: Cultivating Core Meta-Skills with Reinforcement Learning cites this paper.

Teaching LLMs to Self-Evolve: Cultivating Core Meta-Skills with Reinforcement Learning LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-01T06:17:29.782230Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T06:17:29.782230Z digest=sha256:8ae6f6abfc71352b5263d9311c4306079acbc23791fca60d5053b96daee01cbd

Observation 3508a87c-76e5-4c2d-8369-6cd95c41bad6 · inbound

DiDPO: Diff-in-Diff Policy Optimization for Coding Agent Training cites this paper.

DiDPO: Diff-in-Diff Policy Optimization for Coding Agent Training LeetCodeDataset: A Temporal Dataset for Robust Evaluation and Efficient Training of Code LLMs

Reference 54

Resolution
unresolved
no resolver link, observed 2026-08-10T14:00:53.161982Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:00:53.161982Z digest=sha256:8e0ad1528f94cc045de2f954812c2ee1b7523b2a3d16579729cae6698d15456f