Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-22T05:50:23.111591Z
Paper Citation Record · LEDGER
CLORE: Content-Level Optimization for Reasoning Efficiency
As of 7 August 2026, this Paper Citation Record lists 62 of 62 outbound references and 0 inbound Pith citation observations for arXiv:2605.22211.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
Reference resolution
62 of 62 outbound references displayed
- verified exact46
- verified fuzzy15
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch1
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation 696136e2-793a-455b-b747-29311ac43f46 · outbound
This paper cites L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning.
CLORE: Content-Level Optimization for Reasoning Efficiency L1: Controlling How Long A Reasoning Model Thinks With Reinforcement Learning
Reference 1
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T05:51:08.252527Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a219f3af-9b34-4ba7-995c-20d1c9983099 · outbound
This paper cites Back to basics: Revisiting reinforce-style optimization for learning from human feedback in llms.
CLORE: Content-Level Optimization for Reasoning Efficiency Back to basics: Revisiting reinforce-style optimization for learning from human feedback in llms
Reference 2
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T05:51:09.643715Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f3f1dc8c-8d96-48bb-9328-57bff04c810e · outbound
This paper cites Large Language Models for Mathematical Reasoning: Progresses and Challenges.
CLORE: Content-Level Optimization for Reasoning Efficiency Large Language Models for Mathematical Reasoning: Progresses and Challenges
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.336753Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 31c5df9d-9424-4d79-b38b-8704a5eb24f7 · outbound
This paper cites Training language models to reason efficiently.
CLORE: Content-Level Optimization for Reasoning Efficiency Training language models to reason efficiently
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.112138Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 224733ea-9a8c-4dac-b7c2-f999eb5d9d62 · outbound
This paper cites Trims: Real-time tracking of minimal sufficient length for efficient reasoning via rl.
CLORE: Content-Level Optimization for Reasoning Efficiency Trims: Real-time tracking of minimal sufficient length for efficient reasoning via rl
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.154850Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation ae1a9b08-4d6d-4710-a6f2-a6ce32e1ca6d · outbound
This paper cites Do not think that much for 2+ 3=? on the overthinking of long reasoning models.
CLORE: Content-Level Optimization for Reasoning Efficiency Do not think that much for 2+ 3=? on the overthinking of long reasoning models
Reference 6
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T05:51:09.639829Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 346cb749-5c01-423c-9f43-4a55b660d881 · outbound
This paper cites Large Reasoning Models are not thinking straight: on the unreliability of thinking trajectories.
CLORE: Content-Level Optimization for Reasoning Efficiency Large Reasoning Models are not thinking straight: on the unreliability of thinking trajectories
Reference 7
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.101200Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 32eafdbe-ed52-49a4-b269-446d843604d6 · outbound
This paper cites Stable Reinforcement Learning for Efficient Reasoning.
CLORE: Content-Level Optimization for Reasoning Efficiency Stable Reinforcement Learning for Efficient Reasoning
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.263012Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6a483081-dd8a-49a2-8f83-3101c90ede19 · outbound
This paper cites Competitive Programming with Large Reasoning Models.
CLORE: Content-Level Optimization for Reasoning Efficiency Competitive Programming with Large Reasoning Models
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.235559Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation ff273a58-7581-4528-b33f-ff40300a6d2a · outbound
This paper cites A pragmatic way to measure chain-of-thought monitorability.
CLORE: Content-Level Optimization for Reasoning Efficiency A pragmatic way to measure chain-of-thought monitorability
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.331036Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation e3dfef68-a825-4b1e-a012-266ff45c44ee · outbound
This paper cites Serl: Self-play reinforcement learning for large language models with limited data.
CLORE: Content-Level Optimization for Reasoning Efficiency Serl: Self-play reinforcement learning for large language models with limited data
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.130746Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 7cb99d6b-172d-4a34-bb6d-9828bd4c8ee0 · outbound
This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.
CLORE: Content-Level Optimization for Reasoning Efficiency DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
Reference 12
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T05:51:08.136722Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f5b08414-dbcc-423a-9ff1-ef0a8627550a · outbound
This paper cites Token-budget-aware llm reasoning.
CLORE: Content-Level Optimization for Reasoning Efficiency Token-budget-aware llm reasoning
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T05:51:09.636221Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation cba08d68-2a06-4b28-bdac-ed904a928375 · outbound
This paper cites Don’t overthink it.
CLORE: Content-Level Optimization for Reasoning Efficiency Don’t overthink it
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.142676Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c26f8ae5-43b4-4e0d-96d8-503212b2f10e · outbound
This paper cites Olympiadbench: A challenging benchmark for promoting agi with olympiad-level bilingual multimodal scientific problems.
CLORE: Content-Level Optimization for Reasoning Efficiency Olympiadbench: A challenging benchmark for promoting agi with olympiad-level bilingual multimodal scientific problems
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T05:51:09.632448Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 39b11de7-fe3c-4060-99d6-50b4a948d379 · outbound
This paper cites ThinkDial: An Open Recipe for Controlling Reasoning Effort in Large Language Models.
CLORE: Content-Level Optimization for Reasoning Efficiency ThinkDial: An Open Recipe for Controlling Reasoning Effort in Large Language Models
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.273949Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 16253f30-8ba0-4dbe-b761-451d904dbf7b · outbound
This paper cites Measuring Mathematical Problem Solving With the MATH Dataset.
CLORE: Content-Level Optimization for Reasoning Efficiency Measuring Mathematical Problem Solving With the MATH Dataset
Reference 17
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T05:51:08.240716Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c5db1169-5707-4a80-aa5a-ba3caab3c296 · outbound
This paper cites ThinkPrune: Pruning Long Chain-of-Thought of LLMs via Reinforcement Learning.
CLORE: Content-Level Optimization for Reasoning Efficiency ThinkPrune: Pruning Long Chain-of-Thought of LLMs via Reinforcement Learning
Reference 18
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T05:51:08.194772Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 431148f9-675c-4a10-9613-22cf74339235 · outbound
This paper cites REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage Normalization.
CLORE: Content-Level Optimization for Reasoning Efficiency REINFORCE++: Stabilizing Critic-Free Policy Optimization with Global Advantage Normalization
Reference 19
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-22T05:51:08.176467Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 74116fa5-988b-43ce-bb4d-16c06f6f1e5a · outbound
This paper cites Adactrl: Towards adaptive and controllable reasoning via difficulty-aware budgeting.
CLORE: Content-Level Optimization for Reasoning Efficiency Adactrl: Towards adaptive and controllable reasoning via difficulty-aware budgeting
Reference 20
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.246949Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0118d74e-cf98-4043-9d2a-e5f689968498 · outbound
This paper cites OpenAI o1 System Card.
CLORE: Content-Level Optimization for Reasoning Efficiency OpenAI o1 System Card
Reference 21
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T05:51:08.124080Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 19df6ec6-2eff-47be-9bbd-c416dfee3730 · outbound
This paper cites What makes a good reasoning chain? uncovering structural patterns in long chain-of- thought reasoning.
CLORE: Content-Level Optimization for Reasoning Efficiency What makes a good reasoning chain? uncovering structural patterns in long chain-of- thought reasoning
Reference 22
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T05:51:09.624019Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 39a54a02-be9f-4515-8867-7d29dbf3f6ee · outbound
This paper cites Reasoning models sometimes output illegible chains of thought.
CLORE: Content-Level Optimization for Reasoning Efficiency Reasoning models sometimes output illegible chains of thought
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.188963Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation dbe2568e-3262-41ea-9660-a72c084b39ed · outbound
This paper cites Prover-Verifier Games improve legibility of LLM outputs.
CLORE: Content-Level Optimization for Reasoning Efficiency Prover-Verifier Games improve legibility of LLM outputs
Reference 24
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.304679Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0e75ef50-2165-48f8-841c-ac2073259dff · outbound
This paper cites Overthink: Slowdown attacks on reasoning llms.
CLORE: Content-Level Optimization for Reasoning Efficiency Overthink: Slowdown attacks on reasoning llms
Reference 25
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.311073Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 085487de-aad0-4b62-9c98-f0a3253bf1f6 · outbound
This paper cites Solving quan- titative reasoning problems with language models.Advances in neural information processing systems, 35:3843–3857.
CLORE: Content-Level Optimization for Reasoning Efficiency Solving quan- titative reasoning problems with language models.Advances in neural information processing systems, 35:3843–3857
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T05:51:09.664501Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 5d88afe3-db78-4c7c-8106-7475dddf4cd3 · outbound
This paper cites AALC: Large Language Model Efficient Reasoning via Adaptive Accuracy-Length Control.
CLORE: Content-Level Optimization for Reasoning Efficiency AALC: Large Language Model Efficient Reasoning via Adaptive Accuracy-Length Control
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.318894Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 4fc68512-6158-45dc-bcad-f86df5b9b6ac · outbound
This paper cites When Thinking Fails: The Pitfalls of Reasoning for Instruction-Following in LLMs.
CLORE: Content-Level Optimization for Reasoning Efficiency When Thinking Fails: The Pitfalls of Reasoning for Instruction-Following in LLMs
Reference 28
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.363458Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation e5695cff-874d-4959-94b1-58412102b4c5 · outbound
This paper cites SelfBudgeter: Adaptive Token Allocation for Efficient LLM Reasoning.
CLORE: Content-Level Optimization for Reasoning Efficiency SelfBudgeter: Adaptive Token Allocation for Efficient LLM Reasoning
Reference 29
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T05:51:08.290592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c842b863-0d1c-41fc-b1be-fe86ac67373f · outbound
This paper cites Let’s verify step by step.
CLORE: Content-Level Optimization for Reasoning Efficiency Let’s verify step by step
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T05:51:09.655637Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9473f81e-b1c1-4bbf-b0f4-d52050b385e9 · outbound
This paper cites Learn to Reason Efficiently with Adaptive Length-based Reward Shaping.
CLORE: Content-Level Optimization for Reasoning Efficiency Learn to Reason Efficiently with Adaptive Length-based Reward Shaping
Reference 31
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.161581Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 74d3c4ab-bd87-4b13-b6f7-b7548cf70742 · outbound
This paper cites Does Faithfulness-Guided Alignment Hurt Accuracy? Unlocking Accurate and Faithful Post-Retrieval Reasoning.
CLORE: Content-Level Optimization for Reasoning Efficiency Does Faithfulness-Guided Alignment Hurt Accuracy? Unlocking Accurate and Faithful Post-Retrieval Reasoning
Reference 32
- Resolution
- verified exact
- arxiv_id, observed 2026-07-28T02:21:37.675319Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 54861ffc-569e-4c96-872a-45c508107e2a · outbound
This paper cites O1-Pruner: Length-Harmonizing Fine-Tuning for O1-Like Reasoning Pruning.
CLORE: Content-Level Optimization for Reasoning Efficiency O1-Pruner: Length-Harmonizing Fine-Tuning for O1-Like Reasoning Pruning
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.358986Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 509ff2d1-7256-4c24-9bb9-397838723096 · outbound
This paper cites Concise Thoughts: Impact of Output Length on LLM Reasoning and Cost.
CLORE: Content-Level Optimization for Reasoning Efficiency Concise Thoughts: Impact of Output Length on LLM Reasoning and Cost
Reference 34
- Resolution
- verified exact
- arxiv_id, observed 2026-07-28T01:22:17.782417Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 16acf123-3bf2-42ff-b3ad-57f5947b3fb5 · outbound
This paper cites Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744.
CLORE: Content-Level Optimization for Reasoning Efficiency Training language models to follow instructions with human feedback.Advances in neural information processing systems, 35:27730–27744
Reference 35
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T05:51:09.648048Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 8b138a4d-fbef-4a8b-8f81-d604cab1da11 · outbound
This paper cites Revisiting Overthinking in Long Chain-of-Thought from the Perspective of Self-Doubt.
CLORE: Content-Level Optimization for Reasoning Efficiency Revisiting Overthinking in Long Chain-of-Thought from the Perspective of Self-Doubt
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.285565Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation ed965ed0-c2fa-4110-81e7-92c5839ae32f · outbound
This paper cites Direct preference optimization: Your language model is secretly a reward model.
CLORE: Content-Level Optimization for Reasoning Efficiency Direct preference optimization: Your language model is secretly a reward model
Reference 37
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T05:51:09.659756Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 04da9fa2-9cdb-4e1b-b916-759112367174 · outbound
This paper cites A principled approach to chain-of-thought monitorability in reasoning models.
CLORE: Content-Level Optimization for Reasoning Efficiency A principled approach to chain-of-thought monitorability in reasoning models
Reference 38
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T05:51:09.673168Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b69ac798-fe59-4f60-8192-591d2afd54a0 · outbound
This paper cites Measuring Weak-to-Strong Legibility of Reasoning Models.
CLORE: Content-Level Optimization for Reasoning Efficiency Measuring Weak-to-Strong Legibility of Reasoning Models
Reference 39
- Resolution
- verified exact
- arxiv_id, observed 2026-06-03T02:05:14.472947Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 91a6268e-084b-4122-902f-d6a2f4565195 · outbound
This paper cites Proximal Policy Optimization Algorithms.
CLORE: Content-Level Optimization for Reasoning Efficiency Proximal Policy Optimization Algorithms
Reference 40
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T05:51:08.219123Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 919aa59d-b83f-45e4-afef-ba8e432d1ae4 · outbound
This paper cites DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models.
CLORE: Content-Level Optimization for Reasoning Efficiency DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language Models
Reference 41
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T05:51:08.117873Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f1e542d4-bdda-4a54-853a-dcf3a992cc5b · outbound
This paper cites Thinking Fast and Right: Balancing Accuracy and Reasoning Length with Adaptive Rewards.
CLORE: Content-Level Optimization for Reasoning Efficiency Thinking Fast and Right: Balancing Accuracy and Reasoning Length with Adaptive Rewards
Reference 42
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.229808Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation c759b76b-4160-4d13-9665-f0ffd6ae6d1a · outbound
This paper cites Between Underthinking and Overthinking: An Empirical Study of Reasoning Length and correctness in LLMs.
CLORE: Content-Level Optimization for Reasoning Efficiency Between Underthinking and Overthinking: An Empirical Study of Reasoning Length and correctness in LLMs
Reference 43
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.202504Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 5febb1a8-d301-4ebc-a389-4c740c9e2363 · outbound
This paper cites Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models.
CLORE: Content-Level Optimization for Reasoning Efficiency Stop Overthinking: A Survey on Efficient Reasoning for Large Language Models
Reference 44
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T05:51:08.224443Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation ad8dc005-2bfb-4a1a-adb9-3eb8540858fe · outbound
This paper cites Self-Consistency Improves Chain of Thought Reasoning in Language Models.
CLORE: Content-Level Optimization for Reasoning Efficiency Self-Consistency Improves Chain of Thought Reasoning in Language Models
Reference 45
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T05:51:08.299503Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6e0d3468-06de-41e0-9271-260107112612 · outbound
This paper cites Chain-of-thought prompting elicits reasoning in large language models.
CLORE: Content-Level Optimization for Reasoning Efficiency Chain-of-thought prompting elicits reasoning in large language models
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T05:51:09.628822Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 421645f1-8c4f-4f5e-ae2a-4734beba09e2 · outbound
This paper cites Neural Text Generation with Unlikelihood Training.
CLORE: Content-Level Optimization for Reasoning Efficiency Neural Text Generation with Unlikelihood Training
Reference 47
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.106790Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 6c900aeb-fc8e-43ab-b7b3-1eeffbfc8ac2 · outbound
This paper cites How Easily do Irrelevant Inputs Skew the Responses of Large Language Models?.
CLORE: Content-Level Optimization for Reasoning Efficiency How Easily do Irrelevant Inputs Skew the Responses of Large Language Models?
Reference 48
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.168132Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation bc70a0c9-434d-41fc-974f-74b610629371 · outbound
This paper cites The art of efficient reasoning: Data, reward, and optimization.
CLORE: Content-Level Optimization for Reasoning Efficiency The art of efficient reasoning: Data, reward, and optimization
Reference 49
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.207944Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation ab2e150e-adc7-40bf-a0b0-df3f8e5ab3c4 · outbound
This paper cites When More is Less: Understanding Chain-of-Thought Length in LLMs.
CLORE: Content-Level Optimization for Reasoning Efficiency When More is Less: Understanding Chain-of-Thought Length in LLMs
Reference 50
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.368496Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 07878212-db95-4bed-acb5-058a6488d63c · outbound
This paper cites Just Enough Thinking: Efficient Reasoning with Adaptive Length Penalties Reinforcement Learning.
CLORE: Content-Level Optimization for Reasoning Efficiency Just Enough Thinking: Efficient Reasoning with Adaptive Length Penalties Reinforcement Learning
Reference 51
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.348019Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 645af4cb-bb17-447d-8d33-d1bb2b065373 · outbound
This paper cites Qwen3 Technical Report.
CLORE: Content-Level Optimization for Reasoning Efficiency Qwen3 Technical Report
Reference 52
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T05:51:08.353420Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 295a31f4-000d-4951-b416-7d4773872f28 · outbound
This paper cites Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement.
CLORE: Content-Level Optimization for Reasoning Efficiency Qwen2.5-Math Technical Report: Toward Mathematical Expert Model via Self-Improvement
Reference 53
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T05:51:08.213615Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 16f49b6f-1fda-4747-97db-9ffa03026572 · outbound
This paper cites How is llm reasoning distracted by irrelevant context? an analysis using a controlled benchmark.
CLORE: Content-Level Optimization for Reasoning Efficiency How is llm reasoning distracted by irrelevant context? an analysis using a controlled benchmark
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T05:51:09.677288Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 9d78fcb7-d874-4469-a8a3-9bb4853c3314 · outbound
This paper cites Tree of thoughts: Deliberate problem solving with large language models.Ad- vances in neural information processing systems, 36:11809–11822.
CLORE: Content-Level Optimization for Reasoning Efficiency Tree of thoughts: Deliberate problem solving with large language models.Ad- vances in neural information processing systems, 36:11809–11822
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T05:51:09.668785Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 447ab622-07c5-4372-9006-d28a11828813 · outbound
This paper cites Demystifying Long Chain-of-Thought Reasoning in LLMs.
CLORE: Content-Level Optimization for Reasoning Efficiency Demystifying Long Chain-of-Thought Reasoning in LLMs
Reference 56
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T05:51:08.341989Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation b059e8a6-2dcc-44f0-8aa3-480a6d9bb842 · outbound
This paper cites Shorterbetter: Guiding reasoning models to find optimal inference length for efficient reasoning.
CLORE: Content-Level Optimization for Reasoning Efficiency Shorterbetter: Guiding reasoning models to find optimal inference length for efficient reasoning
Reference 57
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.326126Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 5a107780-3a89-421e-830f-1d5928574bbb · outbound
This paper cites DAPO: An Open-Source LLM Reinforcement Learning System at Scale.
CLORE: Content-Level Optimization for Reasoning Efficiency DAPO: An Open-Source LLM Reinforcement Learning System at Scale
Reference 58
- Resolution
- verified exact
- local_arxiv, observed 2026-05-22T05:51:08.372998Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation e343ea59-7990-4620-a66e-cb574e7e7e5c · outbound
This paper cites Efficient rl training for reasoning models via length-aware optimization.
CLORE: Content-Level Optimization for Reasoning Efficiency Efficient rl training for reasoning models via length-aware optimization
Reference 59
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.148451Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation a800ada9-b08c-4d74-81c5-45374ca74d75 · outbound
This paper cites find the time 1000 days later.
CLORE: Content-Level Optimization for Reasoning Efficiency find the time 1000 days later
Reference 60
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T05:51:08.258007Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 30787a6b-254f-48a2-831c-b87e5c07c63d · outbound
This paper cites Python verification.
CLORE: Content-Level Optimization for Reasoning Efficiency Python verification
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T05:51:09.651803Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation f8288a8c-7250-4e12-921e-74733b6a8423 · outbound
This paper cites The possible sums he can end up with are125, 126, 127.
CLORE: Content-Level Optimization for Reasoning Efficiency The possible sums he can end up with are125, 126, 127
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-22T05:51:09.619306Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Pith citing papers
No inbound Pith citation observations are available.