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Boi Faltings

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Related publications (160)

Page 3 of 8

Exploring Defeasibility in Causal Reasoning

Boi Faltings, Antoine Bosselut, Debjit Paul, Shaobo Cui, Mahammad Ismayilzada, 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

Ensuring Privacy through Distributed Computation in Multiple-Depot Vehicle Routing Problems

Boi Faltings, Thomas Léauté, Brammert Ottens

The Vehicle Routing Problem (VRP) has been extensively studied over the last twenty years, because it is an abstraction of many real-life logistics problems. In its multiple-depot variant (MDVRP), the routes of vehicles located at various depots must be op ...

2010

Reporting incentives and biases in online review forums

Boi Faltings, Radu Jurca, Florent Frédéric Garcin

Online reviews have become increasingly popular as a way to judge the quality of various products and services. However, recent work demonstrates that the absence of reporting incentives leads to a biased set of reviews that may not reflect the true qualit ...

2010

Multi-Dimensional Explanation of Target Variables from Documents

Boi Faltings, Diego Matteo Antognini, Claudiu-Cristian Musat

Automated predictions require explanations to be interpretable by humans. Past work used attention and rationale mechanisms to find words that predict the target variable of a document. Often though, they result in a tradeoff between noisy explanations or ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2021

The lookahead principle for preference elicitation: Experimental results

Boi Faltings, Pearl Pu Faltings, Paolo Viappiani

Preference-based search is the problem of finding an item that matches best with a user's preferences. User studies show that example-based tools for preference-based search can achieve significantly higher accuracy when they are complemented with suggesti ...

Springer Verlag2006

Slim: Explicit Slot-Intent Mapping With Bert For Joint Multi-Intent Detection And Slot Filling

Boi Faltings, Fei Mi

Utterance-level intent detection and token-level slot filling are two key tasks for spoken language understanding (SLU) in task-oriented systems. Most existing approaches assume that only a single intent exists in an utterance. However, there are often mul ...

IEEE2022

Addressing fairness in classification with a model-agnostic multi-objective algorithm

Boi Faltings, Diego Matteo Antognini, Claudiu-Cristian Musat

The goal of fairness in classification is to learn a classifier that does not discriminate against groups of individuals based on sensitive attributes, such as race and gender. One approach to designing fair algorithms is to use relaxations of fairness not ...

2021

Mechanisms for Making Crowds Truthful

Boi Faltings, Radu Jurca

We consider schemes for obtaining truthful reports on a common but hidden signal from large groups of rational, self-interested agents. One example are online feedback mechanisms, where users provide observations about the quality of a product or service s ...

AI Access Foundation2009

Differentially private multi-agent constraint optimization

Boi Faltings, Sujit Prakash Gujar, Aleksei Triastcyn, Sankarshan Damle

Distributed constraint optimization (DCOP) is a framework in which multiple agents with private constraints (or preferences) cooperate to achieve a common goal optimally. DCOPs are applicable in several multi-agent coordination/allocation problems, such as ...

Springer2024

Fast Multi-Step Critiquing for VAE-based Recommender Systems

Boi Faltings, Diego Matteo Antognini

Recent studies have shown that providing personalized explanations alongside recommendations increases trust and perceived quality. Furthermore, it gives users an opportunity to refine the recommendations by critiquing parts of the explanations. On one han ...

ASSOC COMPUTING MACHINERY2021

Incentive Schemes for Participatory Sensing

Boi Faltings, Goran Radanovic

We consider a participatory sensing scenario where a group of private sensors observes the same phenomenon, such as air pollution. Since sensors need to be installed and maintained, owners of sensors are inclined to provide inaccurate or random data. We de ...

2015

GameWikiSum: a Novel Large Multi-Document Summarization Dataset

Boi Faltings, Diego Matteo Antognini

Today's research progress in the field of multi-document summarization is obstructed by the small number of available datasets. Since the acquisition of reference summaries is costly, existing datasets contain only hundreds of samples at most, resulting in ...

EUROPEAN LANGUAGE RESOURCES ASSOC-ELRA2020

A :) Is Worth a Thousand Words: How People Attach Sentiment to Emoticons and Words in Tweets

Boi Faltings, Pearl Pu Faltings, Claudiu-Cristian Musat, Marina Boia

Emoticons are widely used to express positive or negative sentiment on Twitter. We report on a study with live users to determine whether emoticons are used to merely emphasize the sentiment of tweets, or whether they are the main elements carrying the sen ...

IEEE2013

Reaching Correlated Equilibria Through Multi-agent Learning

Boi Faltings, Ludek Cigler

Many games have undesirable Nash equilibria. For exam- ple consider a resource allocation game in which two players compete for an exclusive access to a single resource. It has three Nash equilibria. The two pure-strategy NE are effi- cient, but not fair. ...

2011

Tackling Peer-to-Peer Discrimination in the Sharing Economy

Boi Faltings, Naman Goel

Sharing economy platforms such as Airbnb and Uber face a major challenge in the form of peer-to-peer discrimination based on sensitive personal attributes such as race and gender. As shown by a recent study under controlled settings, reputation systems can ...

ACM2020

Personalized News Recommendation with Context Trees

Boi Faltings, Christos Dimitrakakis, Florent Frédéric Garcin

The proliferation of online news creates a need for filtering interesting articles. Compared to other products, however, recommending news has specific challenges: news preferences are subject to trends, users do not want to see multiple articles with simi ...

2013

Assistive Recipe Editing through Critiquing

Boi Faltings, Diego Matteo Antognini

There has recently been growing interest in the automatic generation of cooking recipes that satisfy some form of dietary restrictions, thanks in part to the availability of online recipe data. Prior studies have used pre-trained language models, or relied ...

2022

Blockchain-based Practical Multi-agent Secure Comparison and its Application in Auctions

Boi Faltings, Sujit Prakash Gujar, Sankarshan Damle

AI applications find widespread use in a variety of domains. For further acceptance, mostly when multiple agents interact with the system, we must aim to preserve the privacy of participants information in such applications. Towards this, the Yao’s Million ...

ACM2022

Federated Generative Privacy

Boi Faltings, Aleksei Triastcyn

We propose FedGP, a framework for privacy-preserving data release in the federated learning setting. We use generative adversarial networks, generator components of which are trained by FedAvg algorithm, to draw private artificial data samples and empirica ...

IEEE COMPUTER SOC2020

Incentives for Subjective Evaluations with Private Beliefs

Boi Faltings, Goran Radanovic

The modern web critically depends on aggregation of information from self-interested agents, for example opinion polls, product ratings, or crowdsourcing. We consider a setting where multiple objects (questions, products, tasks) are evaluated by a group of ...

2015