Skip to content
Papers.

When Thoughts Meet Facts: Reusable Reasoning for Long-Context LMs research paper by Amazon, 2025

Amazon · Oct 8, 2025 · Reasoning · 3 citations · 49 upvotes · unverified

Read on arXiv

What it shows

Thought templates enhance long-context language models by structuring evidence combination and guiding multi-hop inference, leading to consistent performance improvements across various benchmarks.

UnverifiedHugging Face's summary; not yet checked by hand.

More from Amazon

All 6
PaperCitations
Don't Mask the Environment: Observation Supervision Changes How Agents Explore Under RLAgent trajectories record what an agent does and what happens next.Agents and evaluation · Sep 2026 · Unverified0
VIDEOP2R: Video Understanding from Perception to ReasoningVideoP2R, a process-aware reinforcement fine-tuning framework, improves video reasoning and understanding by modeling perception and reasoning separately, achieving state-of-the-art results on multiple benchmarks.Reasoning · Nov 2025 · Unverified9
Adaptive Multi-Agent Response Refinement in Conversational SystemsA multi-agent framework enhances conversational quality by refining responses through agents responsible for factuality, personalization, and coherence, outperforming existing methods on challenging datasets.Agents and evaluation · Nov 2025 · Unverified3
Chronos-2: From Univariate to Universal ForecastingChronos-2, a pretrained model with a group attention mechanism, achieves state-of-the-art performance in zero-shot univariate, multivariate, and covariate-informed forecasting tasks.Inference and efficiency · Oct 2025 · Unverified178
TaTToo: Tool-Grounded Thinking PRM for Test-Time Scaling in Tabular ReasoningTaTToo, a novel table-grounded Process Reward Model, enhances tabular reasoning by explicitly addressing table-specific operations and integrating tool-based verification, leading to significant performance improvements over existing PRMs.Reasoning · Oct 2025 · Unverified12

Other reasoning papers

Topic
PaperCitations
Chain-of-Thought Prompting Elicits Reasoning in Large Language ModelsAsking a model to write out its intermediate steps (chain of thought) sharply improves its math and logic answers.Google · Jan 202222.1k
DeepSeekMath: Pushing the Limits of Mathematical Reasoning in Open Language ModelsDeepSeekMath 7B improves mathematical reasoning through enhanced data pre-training and Group Relative Policy Optimization, achieving high scores on MATH benchmark without external tools.DeepSeek · Feb 2024 · Unverified8,994
DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement LearningReinforcement learning taught a model long step-by-step reasoning on par with OpenAI o1.DeepSeek · Jan 20255,694
DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code IntelligenceDeepSeek-Coder-V2, a Mixture-of-Experts language model, excels in code-specific tasks by enhancing coding and mathematical reasoning capabilities while expanding language support and context length.DeepSeek · Jun 2024 · Unverified502
MolmoAct: Action Reasoning Models that can Reason in SpaceAction Reasoning Models (ARMs) integrate perception, planning, and control to enable adaptable and explainable robotic behavior, achieving superior performance across various tasks and settings.Ai2 · Aug 2025 · Unverified185
ThinkAct: Vision-Language-Action Reasoning via Reinforced Visual Latent PlanningThinkAct, a dual-system framework, uses reinforced visual latent planning to enable few-shot adaptation, long-horizon planning, and self-correction in embodied AI tasks by bridging high-level reasoning with low-level action execution.NVIDIA · Jul 2025 · Unverified172
About this paper
Authors
Soyeong Jeong, Taehee Jung, Sung Ju Hwang and 2 more
arXiv
2510.07499 · PDF
Venue
Annual Meeting of the Association for Computational Linguistics
Citations
3, 0 influential · Semantic Scholar
Upvotes
49 · Hugging Face
Lab
Amazon · on Companies · on Quarterly · on Paydays

Changes

What changed
Influential citationsfirst count: 0Sep 25, 2026
Citationsfirst count: 3Sep 25, 2026
New paperFound by the weekly scan, unverifiedSep 25, 2026

Sources: each lab's own papers and arXiv, with citation and upvote counts from Semantic Scholar and Hugging Face. One-line summaries are for orientation, not a substitute for the paper. Logos via logo.dev; trademarks belong to their owners.

New papers by email

Monday afternoons, only in weeks with new papers from the labs.

Double opt-in. Unsubscribe any time.