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Nadi Tomeh

ACL 2026SIGIR 2026可解释性评测与基准效率与系统
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0 一作 · 2 篇 · ACL 2026 / SIGIR 2026

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2026 顶会论文

2
作者位次 #2/4ACL 2026Poster· Natural Language Processing

T o MM e R - Efficient Entity Mention Detection from Large Language Models

Victor Morand · Nadi Tomeh · Josiane Mothe · Benjamin Piwowarski

摘要

Identifying which text spans refer to entities - mention detection- is both foundational for information extraction and a known performance bottleneck. We introduce ToMMeR, a lightweight model (<300K parameters) probing mention detection capabilities from early LLM layers. Across 13 NER benchmark...

可解释性评测与基准效率与系统OpenReview 项目页
作者位次 #3/5SIGIR 2026Oral· Information Retrieval (Full)

A Voronoi Cell Formulation for Principled Token Pruning in Late-Interaction Retrieval Models

Yash Kankanampati · Yuxuan Zong · Nadi Tomeh · Benjamin Piwowarski · Joseph Le Roux

摘要

Late-interaction models such as ColBERT offer competitive performance across various retrieval tasks but require storing a dense embedding for each document token, leading to a substantial index storage overhead. Past works address this by attempting to prune low-importance token embeddings based...

可解释性效率与系统评测与基准OpenReview

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