2 citations · 2 across the 9 of their papers we have counts for
6 papers · 1 filter
Autoformalizing Argumentative Material Inferences
Xin Quan, Reto Gubelmann, André Freitas
Natural language arguments are compelling before they are formally explicit. A premise supports a claim through defeasible warrants, background commitments, and exception condition…
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…
AbstRAG: Learning to Abstract for Retrieval Problems
Lei Xu, Xin Quan, Daniel Pedronette +1
Retrieval-augmented generation often fails when the query, the document evidence, and the user's intent are expressed at different levels of abstraction. A query may ask about a cl…
Reasoning without Gold Standards: A Proxy-Judge Theory of Autoformalization
Lei Xu, Xin Quan, André Freitas
Autoformalization (AF) requires both prover acceptance and fidelity to an informal source, but prover acceptance alone cannot establish fidelity, and expert-validated reference for…
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…
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…