32 citations · 85 across the 50 of their papers we have counts for
7 papers · 1 filter
SciR: A Controllable Benchmark for Scientific Reasoning in LLMs
Pierre Beckmann, Marco Valentino, Andre Freitas
Three paradigmatic forms of inference recur across scientific reasoning: deduction, induction, and causal abduction. Reliably evaluating LLMs on these in scientific settings is cur…
Neurosymbolic Clinical Trial Matching via LLM-Driven Abduction and Logical Verification
Baiyang Qu, Leonardo Ranaldi, Xi Wang +1
Large Language Models (LLMs) offer a promising path to automate Clinical Trial Matching (CTM), but still struggle with the deterministic verification required for complex eligibili…
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…
Compliance vs. Sensibility: On the Reasoning Controllability in Large Language Models
Xingwei Tan, Marco Valentino, Mahmud Elahi Akhter +3
Large Language Models (LLMs) acquire reasoning capabilities through shared inference patterns in pre-training data, which are further elicited via Chain-of-Thought (CoT). However,…
Decompose-and-Formalise: Recursively Verifiable Natural Language Inference
Xin Quan, Marco Valentino, Louise A. Dennis +1
Recent work has shown that integrating large language models (LLMs) with theorem provers (TPs) in neuro-symbolic pipelines helps with entailment verification and proof-guided refin…
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…
Monotonic Reference-Free Refinement for Autoformalization
Lan Zhang, Marco Valentino, André Freitas
While statement autoformalization has advanced rapidly, full-theorem autoformalization remains largely unexplored. Existing iterative refinement methods in statement autoformalizat…