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8 results for “Chain-of-Thought”

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Demystifying Entropy-based Selection for Chain-of-Thought Compression in Large Reasoning Models

A new arXiv preprint challenges the efficacy of entropy-based pruning for Chain-of-Thought compression, finding no advantage over random pruning across models and tasks, and showing token-level entropy selection works only on math benchmarks due to numeric token properties—not generalizable reasoning heuristics.

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arXiv Computation and Language

Aug 3, 2026

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ThinkReset: Learnable Intermediate Interface Construction for Bounded-Context Long-Horizon Reasoning

A new AI reasoning method called ThinkReset introduces an intermediate interface mechanism to improve long-horizon problem solving under fixed context windows by replacing discarded history and optimizing for post-reset continuation — addressing redundancy, overflow, and premature guessing.

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arXiv Artificial Intelligence

Aug 3, 2026

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SLPO: Scaling Latent Reasoning via a Surrogate Policy

Researchers propose SLPO, a new reinforcement learning method to enable outcome-reward optimization in latent reasoning models—addressing key limitations that previously prevented test-time scaling in continuous-vector-based reasoning systems.

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arXiv Computation and Language

Jul 23, 2026

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CoEvoT: Co-Evolving Chain-of-Thought Prompting for Graph-LLM Reasoning

CoEvoT is a new prompting framework that dynamically updates graph token representations during Chain-of-Thought reasoning, enabling step-wise structural evidence refinement for Graph-LLMs under distribution shift.

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arXiv Computation and Language

Jul 17, 2026

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Reasoning Consistency Scanning: A Framework for Auditing Chain-of-Thought Validity in AI Safety Evaluations

Researchers introduced 'reasoning consistency scanning'—a method to audit whether AI models' chain-of-thought explanations logically align with their final answers in safety evaluation transcripts, without requiring experimental intervention.

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arXiv Artificial Intelligence

Jul 10, 2026

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Kara: Efficient Reasoning LLM Serving via Sliding-Window KV Cache Compression

Kara is a new sliding-window KV cache compression method for reasoning LLMs that improves decoding throughput and reduces memory overhead by selectively preserving flexible-sized semantic chunks of the key-value cache during inference.

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arXiv Computation and Language

Published Jul 3, 2026 · Analyzed Jul 6, 2026

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Fable 5 leaked chain-of-thought in web interface, and the rambling is kind of unsettling and cute

Fable's web interface leaked chain-of-thought, raising concerns about interpretability.

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Reddit r/singularity

Published Jul 2, 2026 · Analyzed Jul 6, 2026

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DiscoLoop: Looping Discrete Embeddings and Continuous Hidden States for Multi-hop Reasoning

Researchers propose a new architecture for multi-hop reasoning tasks in large language models.

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arXiv Computation and Language

Published Jul 2, 2026 · Analyzed Jul 5, 2026