3 papers
cs.CL2024
WikiFactDiff: A Large, Realistic, and Temporally Adaptable Dataset for Atomic Factual Knowledge Update in Causal Language Models
Hichem Ammar Khodja, Frédéric Béchet, Quentin Brabant +2
The factuality of large language model (LLMs) tends to decay over time since events posterior to their training are "unknown" to them. One way to keep models up-to-date could be fa…
cs.CL2023
Investigating the Effect of Relative Positional Embeddings on AMR-to-Text Generation with Structural Adapters
Sebastien Montella, Alexis Nasr, Johannes Heinecke +2
Text generation from Abstract Meaning Representation (AMR) has substantially benefited from the popularized Pretrained Language Models (PLMs). Myriad approaches have linearized the…
cs.CL2022
Dependency Parsing with Backtracking using Deep Reinforcement Learning
Franck Dary, Maxime Petit, Alexis Nasr
Greedy algorithms for NLP such as transition based parsing are prone to error propagation. One way to overcome this problem is to allow the algorithm to backtrack and explore an al…