12 papers
Is Inference Mediated by Distinct Semantic Structures in LLMs? A Mechanistic Interpretation
Nura Aljaafari, Marco Valentino, André Freitas
Predicting a label correctly does not necessarily require representing the operation that produces it. Transformer representations are known to carry label-level information, but w…
GeoMathCode: Understanding Interleaved Math-Code Reasoning for Geometry Problem Solving
Yingji Zhang, Yong Dai, André Freitas
Mathematical reasoning is a hallmark of human intelligence, requiring logical deduction, symbolic manipulation, and abstract thinking. Recent multimodal large language models (MLLM…
Mitigating Content Effects on Reasoning in Language Models through Fine-Grained Activation Steering
Marco Valentino, Geonhee Kim, Dhairya Dalal +2
Large language models (LLMs) exhibit reasoning biases, often conflating content plausibility with formal logical validity. This can lead to wrong inferences in critical domains, wh…
Compartmentalised Agentic Reasoning for Clinical NLI
Maël Jullien, Lei Xu, Marco Valentino +1
Large language models can produce fluent judgments for clinical natural language inference, yet they frequently fail when the decision requires the correct inferential schema rathe…
Inferring Latent Intentions: Attributional Natural Language Inference in LLM Agents
Xin Quan, Jiafeng Xiong, Marco Valentino +1
Attributional inference, the ability to predict latent intentions behind observed actions, is a critical yet underexplored capability for large language models (LLMs) operating in…
Adaptive LLM-Symbolic Reasoning via Dynamic Logical Solver Composition
Lei Xu, Pierre Beckmann, Marco Valentino +1
Neuro-symbolic NLP methods aim to leverage the complementary strengths of large language models and formal logical solvers. However, current approaches are mostly static in nature,…