COLM 2025 Past Math & reasoningLarge language modelsInterpretability
The First Workshop on the Application of LLM Explainability to Reasoning and Planning
XLLM-Reason-Plan
- Submission deadline
- Jun 28, 2025, 23:59 UTC imported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- Auto-imported from the OpenReview venue record on 2026-06-11 — please verify and enrich (topics are keyword-guessed).
Accepted papers (19)
Fetched from OpenReview (v2) on 2026-06-11.
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Angular Steering: Behavior Control via Rotation in Activation Space
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Are General-Purpose LLMs Ready for Planning? A Large- Scale Evaluation in PDDL
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Attributing Response to Context: A Jensen–Shannon Divergence Driven Mechanistic Study of Context Attribution in Retrieval-Augmented Generation
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Before You 〈think/〉, Monitor: Implementing Flavell's Metacognitive Framework in LLMs
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Beyond Autocomplete: Designing CopilotLens Towards Transparent and Explainable AI Coding Agents
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Can LLMs Reason Abstractly Over Math Word Problems Without CoT? Disentangling Abstract Formulation From Arithmetic Computation
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Case-Based Reasoning Enhances the Predictive Power of LLMs in Drug-Drug Interaction
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Disambiguate First, Parse Later: Generating Interpretations for Ambiguity Resolution in Semantic Parsing
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Enhancing Logical Reasoning in Large Language Models through Graph-based Synthetic Data
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Failure by Interference: Language Models Make Balanced Parentheses Errors When Faulty Mechanisms Overshadow Sound Ones
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From Indirect Object Identification to Syllogisms: Exploring Binary Mechanisms in Transformer Circuits
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How Post-Training Reshapes LLMs: A Mechanistic View on Knowledge, Truthfulness, Refusal, and Confidence
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HYBRIDMIND: Meta Selection of Natural Language and Symbolic Language for Enhanced LLM Reasoning
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Latent Chain-of-Thought? Decoding the Depth-Recurrent Transformer
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Reasoning Riddles: How Explainability Reveals Cognitive Limits in Vision-Language Models
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ReCalibrate: RL for Uncertainty-Aware Reasoning in LLMs
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Rethinking (Human) Preference Evaluation of LLM Rationales
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The Geometry of Self-Verification in a Task-Specific Reasoning Model
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When Models Know More Than They Can Explain: Quantifying Knowledge Transfer in Human-AI Collaboration