← Search

Julien Velcin

5 accepted papers

2025

HISTOIRESMORALES: A French Dataset for Assessing Moral Alignment

NAACL 2025long

Aligning language models with human values is crucial, especially as they become more integrated into everyday life. While models are often adapted to user preferences, it is equally important to ensure they align with moral norms and behaviours in real-world social situations. Despite significant p…

2025

Towards Multi-Document Question Answering in Scientific Literature: Pipeline, Dataset, and Evaluation

EMNLP 2025

Question-Answering (QA) systems are vital for rapidly accessing and comprehending information in academic literature.However, some academic questions require synthesizing information across multiple documents. While several prior resources consider multi-document QA, they often do not strictly enfor

2024

When Quantization Affects Confidence of Large Language Models?

NAACL 2024findings

Recent studies introduced effective compression techniques for Large Language Models (LLMs) via post-training quantization or low-bit weight representation. Although quantized weights offer storage efficiency and allow for faster inference, existing works have indicated that quantization might compr…

2021

Monitoring geometrical properties of word embeddings for detecting the emergence of new topics.

EMNLP 2021main

Slow emerging topic detection is a task between event detection, where we aggregate behaviors of different words on short period of time, and language evolution, where we monitor their long term evolution. In this work, we tackle the problem of early detection of slowly emerging new topics. To this…

2020

Gaussian Embedding of Linked Documents from a Pretrained Semantic Space

IJCAI 2020poster

Gaussian Embedding of Linked Documents (GELD) is a new method that embeds linked documents (e.g., citation networks) onto a pretrained semantic space (e.g., a set of word embeddings). We formulate the problem in such a way that we model each document as a Gaussian distribution in the word vector sp…