collaborators

5 papers

cs.AI2025

Interactive Evaluation of Large Language Models for Multi-Requirement Software Engineering Tasks

Dimitrios Rontogiannis, Maxime Peyrard, Nicolas Baldwin +3

Standard single-turn, static benchmarks fall short in evaluating the nuanced capabilities of Large Language Models (LLMs) on complex tasks such as software engineering. In this wor…

cs.CL2025

Localized Cultural Knowledge is Conserved and Controllable in Large Language Models

Veniamin Veselovsky, Berke Argin, Benedikt Stroebl +5

Just as humans display language patterns influenced by their native tongue when speaking new languages, LLMs often default to English-centric responses even when generating in othe…

cs.CV2025

Controlling Latent Diffusion Using Latent CLIP

Jason Becker, Chris Wendler, Peter Baylies +2

Instead of performing text-conditioned denoising in the image domain, latent diffusion models (LDMs) operate in latent space of a variational autoencoder (VAE), enabling more effic…

cs.CL2024

Byte BPE Tokenization as an Inverse string Homomorphism

Saibo Geng, Sankalp Gambhir, Chris Wendler +1

Tokenization is an important preprocessing step in the training and inference of large language models (LLMs). While there has been extensive research on the expressive power of th…

cs.CL2024

Separating Tongue from Thought: Activation Patching Reveals Language-Agnostic Concept Representations in Transformers

Clément Dumas, Chris Wendler, Veniamin Veselovsky +2

A central question in multilingual language modeling is whether large language models (LLMs) develop a universal concept representation, disentangled from specific languages. In th…