| A Implies B: Circuit Analysis in LLMs for Propositional Logical Reasoning |
Handles explicit logical reasoning, internal circuit analysis clarifying the types of logics for internal interpretation |
| Multi-head Transformers Provably Learn Symbolic Multi-step Reasoning via Gradient Descent |
Theoretical guarantee that Transformers can learn multi-step symbolic reasoning |
| Transformers Provably Learn Chain-of-Thought Reasoning with Length Generalization |
Formal results: CoT reasoning provably learned, with length generalization |
| Reasoning by Superposition: A Theoretical Perspective on Chain of Continuous Thought |
Frames continuous thought as superposition, theoretical perspective |
| LogicTree: Improving Complex Reasoning of LLMs via Instantiated Multi-step Synthetic Logical Data |
Multi-step synthetic logical data to improve complex reasoning |
| SynLogic: Synthesizing Verifiable Reasoning Data at Scale |
Large-scale verifiable logical data synthesis, useful for logical generalization |
| Enigmata: Scaling Logical Reasoning in LLMs with Synthetic Verifiable Puzzles |
Uses logical puzzles for scalable, verifiable reasoning |
| Compositional Neural Network Verification via Assume-Guarantee Reasoning |
Assume-Guarantee Reasoning (AGR) for modular verification, aligns with argument structure |
| VeriThoughts: Formal Verification Pipeline |
Combines formal verification with code generation & reasoning |
| Evaluating Program Semantics Reasoning with Type Inference in System F |
Evaluates program semantics reasoning using type theory |
| Reviving DSP for Advanced Theorem Proving |
Advanced theorem proving (ATP) via DSP techniques |
| IneqSearch / Ineq-Comp |
Inequality theorem proving, suitable for argument/strategy structure experiments |
| On Learning Verifiers for Chain-of-Thought Reasoning |
Studies how to learn verifiers for CoT reasoning loops |
| Right for the Right Reasons: Avoiding Reasoning Shortcuts via Prototype-Augmented Neurosymbolic AI |
Focus on neurosymbolic reasoning + bias/shortcut avoidance, ensures faithfulness |
| Grammars of Formal Uncertainty: When to Trust LLMs in Automated Reasoning Tasks |
Introduces formal grammars of uncertainty for trust calibration |
| A Theoretical Study on Bridging Internal Probability and Self-Consistency for LLM Reasoning |
Theoretical link between probability and self-consistency for reasoning |
| SATURN: SAT-based Reinforcement Learning to Unleash Language Model Reasoning |
Combines SAT solvers with RL to improve reasoning efficiency |
| Counterfactual reasoning: an analysis of in-context emergence |
Studies counterfactual reasoning and in-context dynamics |
| Mathematical Reasoning Planning for Language Models |
Planning framework for structured mathematical reasoning |
| DuetGraph: Coarse-to-Fine Knowledge Graph Reasoning |
KG reasoning pipeline, coarse-to-fine |
| K-DeCore: Continual Structured Knowledge Reasoning |
Continual learning for structured knowledge reasoning |
| GRIP: A Graph-Based Reasoning Instruction Producer |
Produces reasoning instructions via graphs |
| Deliberation on Priors: Trustworthy Reasoning of LLMs on Knowledge Graphs |
Explores trustworthy KG reasoning using priors |
| Personalized Decision Modeling: Utility Optimization or Textualized-Symbolic Reasoning |
Decision-making models with symbolic reasoning |
| SymRTLO: Neuron-Inspired Symbolic Reasoning |
Neuron-inspired symbolic reasoning for RTL optimization |
| Composing Global Solutions via Algebraic Objects in Neural Nets |
Uses algebraic objects for compositional global reasoning |
| Multimodal Symbolic Logical Reasoning |
Extends symbolic + logical reasoning into multimodality |
| What’s in Common? Multimodal Models Hallucinate When Reasoning Across Scenes |
MLLM hallucinations in cross-scene reasoning |
| When Thinking Drifts: Evidential Grounding for Robust Video Reasoning |
Addresses drift in multimodal reasoning, grounded in evidence |
| Collective Reasoning in Performative Prediction |
Studies collective reasoning phenomena |
| Scientists’ First Exam: Probing Cognitive Abilities of MLLM |
Probes MLLM cognitive abilities (perception, reasoning, understanding) |
| Can MLLMs Absorb Math Reasoning Abilities from LLMs as Free Lunch? |
Evaluates transfer of math reasoning from LLMs to MLLMs |
| Mechanistic Interpretability of RNNs emulating Hidden Markov Models |
Mechanistic interpretability applied to RNN–HMM dynamics |
| The Non-Linear Representation Dilemma: Is Causal Abstraction Enough for Mechanistic Interpretability? |
Questions limits of causal abstraction in mechanistic interpretability |