25 citations · 27 across the 7 of their papers we have counts for
9 papers
: How to learn from procedural How-to questions
Gautier Dagan, Frank Keller, Alex Lascarides
An agent facing a planning problem can use answers to how-to questions to reduce uncertainty and fill knowledge gaps, helping it solve both current and future tasks. However, their…
Plancraft: an evaluation dataset for planning with LLM agents
Gautier Dagan, Frank Keller, Alex Lascarides
We present Plancraft, a multi-modal evaluation dataset for LLM agents. Plancraft has both a text-only and multi-modal interface, based on the Minecraft crafting GUI. We include the…
CAST: Cross-modal Alignment Similarity Test for Vision Language Models
Gautier Dagan, Olga Loginova, Anil Batra
Vision Language Models (VLMs) are typically evaluated with Visual Question Answering (VQA) tasks which assess a model's understanding of scenes. Good VQA performance is taken as ev…
Getting the most out of your tokenizer for pre-training and domain adaptation
Gautier Dagan, Gabriel Synnaeve, Baptiste Rozière
Tokenization is an understudied and often neglected component of modern LLMs. Most published works use a single tokenizer for all experiments, often borrowed from another model, wi…
Dynamic Planning with a LLM
Gautier Dagan, Frank Keller, Alex Lascarides
While Large Language Models (LLMs) can solve many NLP tasks in zero-shot settings, applications involving embodied agents remain problematic. In particular, complex plans that requ…
Learning the Effects of Physical Actions in a Multi-modal Environment
Gautier Dagan, Frank Keller, Alex Lascarides
Large Language Models (LLMs) handle physical commonsense information inadequately. As a result of being trained in a disembodied setting, LLMs often fail to predict an action's out…
NL-Augmenter: A Framework for Task-Sensitive Natural Language Augmentation
Kaustubh D. Dhole, Varun Gangal, Sebastian Gehrmann +122
Data augmentation is an important component in the robustness evaluation of models in natural language processing (NLP) and in enhancing the diversity of the data they are trained…
Co-evolution of language and agents in referential games
Gautier Dagan, Dieuwke Hupkes, Elia Bruni
Referential games offer a grounded learning environment for neural agents which accounts for the fact that language is functionally used to communicate. However, they do not take i…
Location Attention for Extrapolation to Longer Sequences
Yann Dubois, Gautier Dagan, Dieuwke Hupkes +1
Neural networks are surprisingly good at interpolating and perform remarkably well when the training set examples resemble those in the test set. However, they are often unable to…