40 citations · 124 across the 62 of their papers we have counts for
67 papers
Small sums of roots of unity: polylogarithmic exceptional sets and conditional separation
Qi Cheng
We prove a polylogarithmic exceptional-set estimate for symmetric five-term sums of roots of unity of arbitrary order. More precisely, at most points of the $N…
Faithful Chart Generation for Multimodal Deep Research: Frame-Evidence Co-Adaptation
Yuxin Yue, Yingchen Zhang, Ruqing Zhang +3
Analytical charts in multimodal deep research encode quantitative claims, requiring every visualized value to be faithfully grounded in supporting evidence. Unlike retrieved images…
A Mechanistic Analysis of Gender Sensitivity in Dense Retrieval Models
Catherine Chen, Maarten de Rijke, Carsten Eickhoff
While gender bias in dense retrieval models is well documented, with prior work showing that models often score male-gendered documents higher than female or neutral variants, the…
Lost in Decoding? Reproducing and Stress-Testing the Look-Ahead Prior in Generative Retrieval
Kidist Amde Mekonnen, Yongkang Li, Yubao Tang +2
Generative retrieval (GR) ranks documents by autoregressively generating document identifiers. Because many GR methods rely on trie-constrained beam search, they are vulnerable to…
Cold-Starts in Generative Recommendation: A Reproducibility Study
Zhen Zhang, Jujia Zhao, Xinyu Ma +3
Cold-start recommendation remains a central challenge in dynamic, open-world platforms, requiring models to recommend for newly registered users (user cold-start) and to recommend…
Model Editing for New Document Integration in Generative Information Retrieval
Zhen Zhang, Zihan Wang, Xinyu Ma +6
Generative retrieval (GR) reformulates the Information Retrieval (IR) task as the generation of document identifiers (docIDs). Despite its promise, existing GR models exhibit poor…
Contrastive Learning for Diversity-Aware Product Recommendations in Retail
Vasileios Karlis, Ezgi Yıldırım, David Vos +1
Recommender systems often struggle with long-tail distributions and limited item catalog exposure, where a small subset of popular items dominates recommendations. This challenge i…
Orcheo: A Modular Full-Stack Platform for Conversational Search
Shaojie Jiang, Svitlana Vakulenko, Maarten de Rijke
Conversational search (CS) requires a complex software engineering pipeline that integrates query reformulation, ranking, and response generation. CS researchers currently face two…
The Unfairness of Multifactorial Bias in Recommendation
Masoud Mansoury, Jin Huang, Mykola Pechenizkiy +2
Popularity bias and positivity bias are two prominent sources of bias in recommender systems. Both arise from input data, propagate through recommendation models, and lead to unfai…
Re-Rankers as Relevance Judges
Chuan Meng, Jiqun Liu, Mohammad Aliannejadi +3
Using large language models (LLMs) to predict relevance judgments has shown promising results. Most studies treat this task as a distinct research line, e.g., focusing on prompt de…
Can Small Agents Collaborate to Beat a Single Large Language Model?
Agata Żywot, Xinyi Chen, Yifei Yuan +2
Recent progress in language modeling has largely relied on scaling model size, yet larger models do not reliably improve performance on tasks requiring multi-step reasoning and too…
CLAX: Fast and Flexible Neural Click Models in JAX
Philipp Hager, Onno Zoeter, Maarten de Rijke
CLAX is a JAX-based library that implements classic click models using modern gradient-based optimization. While neural click models have emerged over the past decade, complex clic…
Query Decomposition for RAG: Balancing Exploration-Exploitation
Roxana Petcu, Kenton Murray, Daniel Khashabi +4
Retrieval-augmented generation (RAG) systems address complex user requests by decomposing them into subqueries, retrieving potentially relevant documents for each, and then aggrega…
ZeroGR: A Generalizable and Scalable Framework for Zero-Shot Generative Retrieval
Weiwei Sun, Keyi Kong, Xinyu Ma +5
Generative retrieval (GR) reformulates information retrieval (IR) by framing it as the generation of document identifiers (docids), thereby enabling end-to-end optimization and sea…
LiRA: A Multi-Agent Framework for Reliable and Readable Literature Review Generation
Gregory Hok Tjoan Go, Khang Ly, Anders Søgaard +3
The rapid growth of scientific publications has made it increasingly difficult to keep literature reviews comprehensive and up-to-date. Though prior work has focused on automating…
Does Generative Retrieval Overcome the Limitations of Dense Retrieval?
Yingchen Zhang, Ruqing Zhang, Jiafeng Guo +3
Generative retrieval (GR) has emerged as a new paradigm in neural information retrieval, offering an alternative to dense retrieval (DR) by directly generating identifiers of relev…
A Comprehensive Taxonomy of Negation for NLP and Neural Retrievers
Roxana Petcu, Samarth Bhargav, Maarten de Rijke +1
Understanding and solving complex reasoning tasks is vital for addressing the information needs of a user. Although dense neural models learn contextualised embeddings, they still…
What if Othello-Playing Language Models Could See?
Xinyi Chen, Yifei Yuan, Jiaang Li +3
Language models are often said to face a symbol grounding problem. While some have argued the problem can be solved without resort to other modalities, many have speculated that gr…
Rethinking Click Models in Light of Carousel Interfaces: Theory-Based Categorization and Design of Click Models
Jingwei Kang, Maarten de Rijke, Santiago de Leon-Martinez +1
Click models are a well-established for modeling user interactions with web interfaces. Previous work has mainly focused on traditional single-list web search settings; this includ…
Optimized Text Embedding Models and Benchmarks for Amharic Passage Retrieval
Kidist Amde Mekonnen, Yosef Worku Alemneh, Maarten de Rijke
Neural retrieval methods using transformer-based pre-trained language models have advanced multilingual and cross-lingual retrieval. However, their effectiveness for low-resource,…
DeepShop: A Benchmark for Deep Research Shopping Agents
Yougang Lyu, Xiaoyu Zhang, Lingyong Yan +3
Web agents for online shopping have shown great promise in automating user interactions across e-commerce platforms. Benchmarks for assessing such agents do not reflect the complex…
Lost at the Beginning of Reasoning
Baohao Liao, Xinyi Chen, Sara Rajaee +5
Recent advancements in large language models (LLMs) have significantly advanced complex reasoning capabilities, particularly through extended chain-of-thought (CoT) reasoning that…
The Silent Saboteur: Imperceptible Adversarial Attacks against Black-Box Retrieval-Augmented Generation Systems
Hongru Song, Yu-an Liu, Ruqing Zhang +4
We explore adversarial attacks against retrieval-augmented generation (RAG) systems to identify their vulnerabilities. We focus on generating human-imperceptible adversarial exampl…
Iterative Self-Incentivization Empowers Large Language Models as Agentic Searchers
Zhengliang Shi, Lingyong Yan, Dawei Yin +3
Large language models (LLMs) have been widely integrated into information retrieval to advance traditional techniques. However, effectively enabling LLMs to seek accurate knowledge…