Publications de Debjit Paul | EPFL Graph Search

A Logical Fallacy-Informed Framework for Argument Generation

Boi Faltings, Robert West, Luca Mouchel, Antoine Bosselut, Debjit Paul

Despite the remarkable performance of large language models (LLMs), they still struggle with generating logically sound arguments, resulting in potential risks such as spreading misinformation. An important factor contributing to LLMs' suboptimal performan ...

Association for Computational Linguistics2025

Exploring Defeasibility in Causal Reasoning

Boi Faltings, Antoine Bosselut, Mahammad Ismayilzada, Debjit Paul, Lazar Milikic

Defeasibility in causal reasoning implies that the causal relationship between cause and effect can be strengthened or weakened. Namely, the causal strength between cause and effect should increase or decrease with the incorporation of strengthening argume ...

2024

Making Reasoning Matter: Measuring and Improving Faithfulness of Chain-of-Thought Reasoning

Boi Faltings, Robert West, Antoine Bosselut, Debjit Paul

Large language models (LLMs) have been shown to perform better when asked to reason step-by-step before answering a question. However, it is unclear to what degree the model's final answer is faithful to the stated reasoning steps. In this paper, we perfor ...

Association for Computational Linguistics (ACL)2024

CRAB: Assessing the Strength of Causal Relationships Between Real-World Events

Karl Aberer, Angeliki Romanou, Antoine Bosselut, Debjit Paul, Syrielle Mathilde Marie Montariol, Léo Jules Laugier

Understanding narratives requires reasoning about the cause-and-effect relationships between events mentioned in the text. While existing foundation models yield impressive results in many NLP tasks requiring reasoning, it is unclear whether they understan ...

Association for Computational Linguistics2023

Language Model Decoding as Likelihood–Utility Alignment

Boi Faltings, Maxime Jean Julien Peyrard, Robert West, Martin Josifoski, Valentin Hartmann, Jiheng Wei, Frano Rajic, Debjit Paul

A critical component of a successful language generation pipeline is the decoding algorithm. However, the general principles that should guide the choice of a decoding algorithm re- main unclear. Previous works only compare decoding algorithms in narrow sc ...

Assoc Computational Linguistics-Acl2023

REFINER: Reasoning Feedback on Intermediate Representations

Boi Faltings, Maxime Jean Julien Peyrard, Robert West, Beatriz Maria Borges Ribeiro, Antoine Bosselut, Mahammad Ismayilzada, Debjit Paul

Language models (LMs) have recently shown remarkable performance on reasoning tasks by explicitly generating intermediate inferences, e.g., chain-of-thought prompting. However, these intermediate inference steps may be in- appropriate deductions from the i ...

2023

CRoW: Benchmarking Commonsense Reasoning in Real-World Tasks

Antoine Bosselut, Mahammad Ismayilzada, Debjit Paul, Syrielle Mathilde Marie Montariol

Recent efforts in natural language processing (NLP) commonsense reasoning research have yielded a considerable number of new datasets and benchmarks. However, most of these datasets formulate commonsense reasoning challenges in artificial scenarios that ar ...

Association for Computational Linguistics2023