Publications by Boi Faltings | EPFL Graph Search

Modelleyen: Continual Learning and Planning via Structured Modelling of Environment Dynamics

The current machine learning paradigm relies on continuous representations and fixed neural network architectures to approximate environmental structures, leading to challenges with continual learning, internal structure design, and goal-directed behavior ...

Springer Science and Business Media Deutschland GmbH2025

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

On the Parallels Between Evolutionary Theory and the State of AI

Boi Faltings, Zeki Doruk Erden

This article critically examines the foundational principles of contemporary AI methods, exploring the limitations that hinder its potential. We draw parallels between the modern AI landscape and the 20th-century Modern Synthesis in evolutionary biology, a ...

ACM2025

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

Differentially private multi-agent constraint optimization

Boi Faltings, Aleksei Triastcyn, Sujit Prakash Gujar, 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

Peer Neighborhood Mechanisms: A Framework for Mechanism Generalization

Boi Faltings

Peer prediction incentive mechanisms for crowdsourcing are generally limited to eliciting samples from categorical distributions. Prior work on extending peer prediction to arbitrary distributions has largely relied on assumptions on the structures of the ...

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

Unveiling the Art of Heading Design: A Harmonious Blend of Summarization, Neology, and Algorithm

Boi Faltings

Crafting an appealing heading is crucial for attracting readers and marketing work or products. A popular way is to summarize the main idea with a refined description and a memorable acronym. However, there lacks a systematic study and a formal benchmark i ...

Association for Computational Linguistics2024

The Odyssey of Commonsense Causality: From Foundational Benchmarks to Cutting-Edge Reasoning

Boi Faltings

Understanding commonsense causality is a unique mark of intelligence for humans. It helps people understand the principles of the real world better and benefits the decisionmaking process related to causation. For instance, commonsense causality is crucial ...

Association for Computational Linguistics2024

LIA: Privacy-Preserving Data Quality Evaluation in Federated Learning Using a Lazy Influence Approximation

Boi Faltings, Ljubomir Rokvic

In Federated Learning, it is crucial to handle low-quality, corrupted, or malicious data. However, traditional data valuation methods are not suitable due to privacy concerns. To address this, we propose a simple yet effective approach that utilizes a new ...

Institute of Electrical and Electronics Engineers Inc.2024

Nuance Matters: Probing Epistemic Consistency in Causal Reasoning

Boi Faltings, Luca Mouchel

Previous research on causal reasoning often overlooks the subtleties crucial to understanding causal reasoning. To address this gap, our study introduces the concept of causal epistemic consistency, which focuses on the self-consistency of Large Language M ...

2024

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

A Practical Influence Approximation for Privacy-Preserving Data Filtering in Federated Learning

Boi Faltings, Panayiotis Danassis, Ljubomir Rokvic

Federated Learning by nature is susceptible to low-quality, corrupted, or even malicious data that can severely degrade the quality of the learned model. Traditional techniques for data valuation cannot be applied as the data is never revealed. We present ...

2023

AI-driven Prices for Externalities and Sustainability in Production Markets

Boi Faltings, Panayiotis Danassis, Aris Filos Ratsikas

Traditional competitive markets do not account for negative externalities; indirect costs that some participants impose on others, such as the cost of over-appropriating a common-pool resource (which diminishes future stock, and thus harvest, for everyone) ...

Cornell University2023

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

incentive Mechanism Design for Responsible Data Governance: A Large-Scale Field Experiment

Boi Faltings, Naman Goel

A crucial building block of responsible artificial intelligence is responsible data governance, including data collection. Its importance is also underlined in the latest EU regulations. The data should be of high quality, foremost correct and representati ...

2023

Infochain: A Decentralized, Trustless and Transparent Oracle on Blockchain

Boi Faltings, Naman Goel, Aris Filos Ratsikas

Blockchain based systems allow various kinds of financial transactions to be executed in a decentralized manner. However, these systems often rely on a trusted third party (oracle) to get correct information about the real-world events, which trigger the f ...

2022

Differentially Private Multi-Agent Constraint Optimization

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

Several optimization scenarios involve multiple agents that desire to protect the privacy of their preferences. There are distributed algorithms for constraint optimization that provide improved privacy protection through secure multiparty computation. How ...

ACM2022

ADER: Adaptively Distilled Exemplar Replay Towards Continual Learning for Session-based Recommendation

Boi Faltings, Fei Mi, Xiaoyu Lin

Session-based recommendation has received growing attention recently due to the increasing privacy concern. Despite the recent success of neural session-based recommenders, they are typically developed in an offline manner using a static dataset. However, ...

ACM2022

Toward Mobile Distributed Ledgers

Boi Faltings, Sujit Prakash Gujar, Dimitrios Chatzopoulos, Anurag Jain

Advances in mobile computing have paved the way for new types of distributed applications that can be executed solely by mobile devices on Device-to-Device (D2D) ecosystems (e.g., crowdsensing). Sophisticated applications, like cryptocurrencies, need distr ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2022