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Concept

Commonsense reasoning

Related publications (22)

REFINER: Reasoning Feedback on Intermediate Representations

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

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

Language Model Decoding as Likelihood–Utility Alignment

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

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

Monotonicity Reasoning in the Age of Neural Foundation Models

Zeming Chen

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 ...

Springer2023

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

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

Dimitrios Kyritsis, Jinzhi Lu

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

Textual Explanations and Critiques in Recommendation Systems

Diego Matteo Antognini

Artificial intelligence and machine learning algorithms have become ubiquitous. Although they offer a wide range of benefits, their adoption in decision-critical fields is limited by their lack of interpretability, particularly with textual data. Moreover, ...

EPFL2022

Conversational Multi-Hop Reasoning with Neural Commonsense Knowledge and Symbolic Logic Rules

Antoine Bosselut

One of the challenges faced by conversational agents is their inability to identify unstated presumptions of their users' commands, a task trivial for humans due to their common sense. In this paper, we propose a zeroshot commonsense reasoning system for c ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2021

Efficient Text-based Reinforcement Learning by Jointly Leveraging State and Commonsense Graph Representations

Mattia Atzeni

Text-based games (TBGs) have emerged as useful benchmarks for evaluating progress at the intersection of grounded language understanding and reinforcement learning (RL). Recent work has proposed the use of external knowledge to improve the efficiency of RL ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2021

An Ink–and–Paper Automaton: The Conceptual Mechanization of Cognition and the Practical Automation of Reasoning in Leibniz’s De Affectibus (1679)

Simon François Dumas Primbault

On ten loose handwritten folios dating back from April 1679, Leibniz gradually devised, in the course of three days, a full-blown theory of thought that nonetheless remained unpublished and still has received little attention from scholars. Conceiving of a ...

2020

A Bayesian Model of Individual Differences and Flexibility in Inductive Reasoning for Categorization of Examples

Pierre Dillenbourg, Jennifer Kaitlyn Olsen, Louis Pierre Faucon

Inductive reasoning is an important educational practice but can be difficult for teachers to support in the classroom due to the high level of preparation and classroom time needed to choose the teaching materials that challenge students' current views. I ...

ASSOC COMPUTING MACHINERY2020

Context-Aware Crowd Counting

Pascal Fua, Mathieu Salzmann, Weizhe Liu

State-of-the-art methods for counting people in crowded scenes rely on deep networks to estimate crowd density. They typically use the same filters over the whole image or over large image patches. Only then do they estimate local scale to compensate for p ...

IEEE/CVF2019

Acquiring Broad Commonsense Knowledge for Sentiment Analysis Using Human Computation

Marina Boia

While artificial intelligence is successful in many applications that cover specific domains, for many commonsense problems there is still a large gap with human performance. Automated sentiment analysis is a typical example: while there are techniques tha ...

EPFL2016

Iterative structural identification framework for evaluation of existing structures

Ian Smith, Romain Pasquier

Evaluation of aging infrastructure has been a world-wide concern for decades due to its economic, ecological and societal importance. Existing structures usually have large amounts of unknown reserve capacity that may be evaluated though structural identif ...

2016

Formal verification of infinite-state BIP models

Simon Bliudze, Wajeb Saab

We propose two expressive and complementary techniques for the verification of safety properties of infinite-state BIP models. Both our techniques deal with the full BIP specification, while the existing approaches impose con- siderable restrictions: they ...

Springer2015

Knowledge-based decision support for improving the adaptive product development process

Predrag Spasojevic

The product development process (PDP) is a complex process encompassing many very diverse activities, and involving a fairly big number of actors, spread across different professions, teams and companies. In todayâ s product development, more often than n ...

EPFL2015

Ontology-based approach for context modeling in enterprise applications

Dimitrios Kyritsis, Drazen Nadoveza

Today, enterprise applications provide large amounts of data and finding the right information on time for a given purpose is often a challenge. In these environments, users do not know what information is important, why it is important and finally, how to ...

Elsevier Science Bv2014

Constructing Context-Aware Sentiment Lexicons with an Asynchronous Game with a Purpose

Boi Faltings, Claudiu-Cristian Musat, Marina Boia

One of the reasons sentiment lexicons do not reach human-level performance is that they lack the contexts that define the polarities of words. While obtaining this knowledge through machine learning would require huge amounts of data, context is commonsens ...

Springer-Verlag Berlin2014

Encoding metaknowledge for historical databases

Frédéric Kaplan, Marc-Antoine Nüssli

Historical knowledge is fundamentally uncertain. A given account of an historical event is typically based on a series of sources and on sequences of interpretation and reasoning based on these sources. Generally, the product of this historical research ta ...

2014

Macropores and water flow in soils revisited

The original review of macropores and water flow in soils by Beven and Germann is now 30 years old and has become one of the most highly cited papers in hydrology. This paper attempts to review the progress in observations and theoretical reasoning about p ...

Amer Geophysical Union2013

Decision Procedures for Program Synthesis and Verification

Ruzica Piskac

Decision procedures are widely used in software development and verification. The goal of this dissertation is to increase the scope of properties that can be verified using decision procedures. To achieve this goal, we identify three improvements over the ...

EPFL2011