329 citations · 1.2k across the 61 of their papers we have counts for
4 papers · 2 filters
Effect of Document Packing on the Latent Multi-Hop Reasoning Capabilities of Large Language Models
Gabriele Prato, Shagun Sodhani, Alessandro Sordoni +1
The standard practice for training large language models involves packing multiple documents together to optimize computational efficiency. However, the impact of this process on t…
Gistify! Codebase-Level Understanding via Runtime Execution
Hyunji Lee, Minseon Kim, Chinmay Singh +10
As coding agents are increasingly deployed in large codebases, the need to automatically design challenging, codebase-level evaluation is central. We propose Gistify, a task where…
MedRiskEval: Medical Risk Evaluation Benchmark of Language Models, On the Importance of User Perspectives in Healthcare Settings
Jean-Philippe Corbeil, Minseon Kim, Maxime Griot +4
As the performance of large language models (LLMs) continues to advance, their adoption in the medical domain is increasing. However, most existing risk evaluations largely focused…
A Modular Approach for Clinical SLMs Driven by Synthetic Data with Pre-Instruction Tuning, Model Merging, and Clinical-Tasks Alignment
Jean-Philippe Corbeil, Amin Dada, Jean-Michel Attendu +7
High computation costs and latency of large language models such as GPT-4 have limited their deployment in clinical settings. Small language models (SLMs) offer a cost-effective al…