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Publications associées (90)

SC-TPTP: An Extension of the TPTP Derivation Format for Sequent-Based Calculus

Motivated by the transfer of proofs between proof systems, and in particular from first order automated theorem provers (ATPs) to interactive theorem provers (ITPs), we specify an extension of the TPTP derivation text format to describe proofs in first-ord ...

2024

REFINER: Reasoning Feedback on Intermediate Representations

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

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

Monotonicity Reasoning in the Age of Neural Foundation Models

Zeming Chen, Qiyue Gao

The recent advance of large language models (LLMs) demonstrates that these large-scale foundation models achieve remarkable capabilities across a wide range of language tasks and domains. The success of the statistical learning approach challenges our unde ...

Dordrecht2023

Tree-AMP: Compositional Inference with Tree Approximate Message Passing

Florent Gérard Krzakala, Lenka Zdeborová

We introduce Tree-AMP, standing for Tree Approximate Message Passing, a python package for compositional inference in high-dimensional tree-structured models. The package provides a unifying framework to study several approximate message passing algorithms ...

2023

AiiDA-defects: an automated and fully reproducible workflow for the complete characterization of defect chemistry in functional materials

Nicola Marzari, Sokseiha Muy, Conrad Johnston

Functional materials that enable many technological applications in our everyday lives owe their unique properties to defects that are carefully engineered and incorporated into these materials during processing. However, optimizing and characterizing thes ...

IOP Publishing Ltd2023

Stop Pre-Training: Adapt Visual-Language Models to Unseen Languages

Karl Aberer, Rémi Philippe Lebret, Negar Foroutan Eghlidi

Vision-Language Pre-training (VLP) has advanced the performance of many visionlanguage tasks, such as image-text retrieval, visual entailment, and visual reasoning. The pre-training mostly utilizes lexical databases and image queries in English. Previous w ...

Assoc Computational Linguistics-Acl2023

Deep learning-based analysis of multiple sclerosis lesions with high and ultra-high field MRI

Francesco La Rosa

Multiple sclerosis (MS) is the most common demyelinating disease of the central nervous system and affects almost 3 million people worldwide. There is currently no cure for MS, and its symptoms, starting with fatigue and weakness, often progress over time ...

EPFL2022

A Data-Knowledge Hybrid Driven Method for Gas Turbine Gas Path Diagnosis

Jinzhi Lu, Xiaochen Zheng, Jinwei Chen

Gas path fault diagnosis of a gas turbine is a complex task involving field data analysis and knowledge-based reasoning. In this paper, a data-knowledge hybrid driven method for gas path fault diagnosis is proposed by integrating a physical model-based gas ...

MDPI2022

Scaling Language Features for Program Verification

Georg Stefan Schmid

Formal verification of real-world software systems remains challenging for a number of reasons, including lack of automation, friction in specifying properties, and limited support for the diverse programming paradigms used in industry. In this thesis we m ...

EPFL2022

Automated approach for the evaluation of glutathione-S-transferase P1-1 inhibition by organometallic anticancer compounds

Paul Joseph Dyson, Sarah Alexandra Pais Pereira

A novel automated method based on sequential injection analysis (SIA), a non-segmented flow injection technique, was developed to evaluate glutathione S-transferase P1-1 (GST P1-1) activity in the presence of organometallic complexes with putative anticanc ...

TAYLOR & FRANCIS LTD2022

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