SEA: Search Engines Amsterdam

This meetup session will focus on ACL and SIGIR 2026 and feature three speakers from University of Amsterdam: Yibin Lei, Zahra Abbasiantaeb and Dylan Jia-Huei Ju. They will present their papers accepted at ACL and SIGIR 2026.

Location: Science Park 904, Room C3.161
Date: Friday, June 26
Time: 16:00-17:00
Zoom link: https://uva-live.zoom.us/j/65011610507

Details below:
Speaker #1: Yibin Lei

Title: Making Large Language Models Efficient Dense Retrievers
Abstract: Recent work has shown that directly fine-tuning large language models (LLMs) for dense retrieval yields strong performance, but their substantial parameter counts make them computationally inefficient. While prior studies have revealed significant layer redundancy in LLMs for generative tasks, it remains unclear whether similar redundancy exists when these models are adapted for retrieval tasks, which require encoding entire sequences into fixed representations rather than generating tokens iteratively. To this end, we conduct a comprehensive analysis of layer redundancy in LLM-based dense retrievers. We find that, in contrast to generative settings, MLP layers are substantially more prunable, while attention layers remain critical for semantic aggregation. Building on this insight, we propose EffiR, a framework for developing efficient retrievers that performs large-scale MLP compression through a coarse-to-fine strategy (coarse-grained depth reduction followed by fine-grained width reduction), combined with retrieval-specific fine-tuning. Across diverse BEIR datasets and LLM backbones, EffiR achieves substantial reductions in model size and inference cost while preserving the performance of full-size models.
Bio: Yibin Lei is a PhD student at the University of Amsterdam, where he works on information retrieval in multilingual and low-resource scenarios.He has co-authored multiple papers in leading conferences like ACL,