9 papers
DRIFT: Decompose, Retrieve, Illustrate, then Formalize Theorems
Meiru Zhang, Philipp Borchert, Milan Gritta +1
Automating the formalization of mathematical statements for theorem proving remains a major challenge for Large Language Models (LLMs). LLMs struggle to identify and utilize the pr…
A Benchmark for Deep Information Synthesis
Debjit Paul, Daniel Murphy, Milan Gritta +14
Large language model (LLM)-based agents are increasingly used to solve complex tasks involving tool use, such as web browsing, code execution, and data analysis. However, current e…
SparsePO: Controlling Preference Alignment of LLMs via Sparse Token Masks
Fenia Christopoulou, Ronald Cardenas, Gerasimos Lampouras +2
Direct alignment algorithms have proven an effective step for aligning language models to human-desired behaviors. Current variants of the Direct Preference Optimization objective…
Conjecturing: An Overlooked Step in Formal Mathematical Reasoning
Jasivan Alex Sivakumar, Philipp Borchert, Ronald Cardenas +1
Autoformalisation, the task of expressing informal mathematical statements in formal language, is often viewed as a direct translation process. This, however, disregards a critical…
TopoAlign: A Framework for Aligning Code to Math via Topological Decomposition
Yupei Li, Philipp Borchert, Gerasimos Lampouras
Large Language Models (LLMs) excel at both informal and formal (e.g. Lean 4) mathematical reasoning but still struggle with autoformalisation, the task of transforming informal int…
Human-inspired Episodic Memory for Infinite Context LLMs
Zafeirios Fountas, Martin A Benfeghoul, Adnan Oomerjee +4
Large language models (LLMs) have shown remarkable capabilities, but still struggle with processing extensive contexts, limiting their ability to maintain coherence and accuracy ov…