13 citations · 13 across the 8 of their papers we have counts for
8 papers
FollowTable: A Benchmark for Instruction-Following Table Retrieval
Rihui Jin, Yuchen Lu, Ting Zhang +7
Table Retrieval (TR) has traditionally been formulated as an ad-hoc retrieval problem, where relevance is primarily determined by topical semantic similarity. With the growing adop…
All Roads Lead to Rome: Unveiling the Trajectory of Recommender Systems Across the LLM Era
Bo Chen, Xinyi Dai, Huifeng Guo +9
Recommender systems (RS) are vital for managing information overload and delivering personalized content, responding to users' diverse information needs. The emergence of large lan…
CoIR: A Comprehensive Benchmark for Code Information Retrieval Models
Xiangyang Li, Kuicai Dong, Yi Quan Lee +5
Despite the substantial success of Information Retrieval (IR) in various NLP tasks, most IR systems predominantly handle queries and corpora in natural language, neglecting the dom…
Evaluating the External and Parametric Knowledge Fusion of Large Language Models
Hao Zhang, Yuyang Zhang, Xiaoguang Li +8
Integrating external knowledge into large language models (LLMs) presents a promising solution to overcome the limitations imposed by their antiquated and static parametric memory.…
CtrlA: Adaptive Retrieval-Augmented Generation via Inherent Control
Huanshuo Liu, Hao Zhang, Zhijiang Guo +6
Retrieval-augmented generation (RAG) has emerged as a promising solution for mitigating hallucinations of large language models (LLMs) with retrieved external knowledge. Adaptive R…
Planning with Multi-Constraints via Collaborative Language Agents
Cong Zhang, Derrick Goh Xin Deik, Dexun Li +2
The rapid advancement of neural language models has sparked a new surge of intelligent agent research. Unlike traditional agents, large language model-based agents (LLM agents) hav…
Multi-view Content-aware Indexing for Long Document Retrieval
Kuicai Dong, Derrick Goh Xin Deik, Yi Quan Lee +4
Long document question answering (DocQA) aims to answer questions from long documents over 10k words. They usually contain content structures such as sections, sub-sections, and pa…
Parameter-Efficient Conversational Recommender System as a Language Processing Task
Mathieu Ravaut, Hao Zhang, Lu Xu +2
Conversational recommender systems (CRS) aim to recommend relevant items to users by eliciting user preference through natural language conversation. Prior work often utilizes exte…