2 citations · 2 across the 6 of their papers we have counts for
6 papers
AttentionRetriever: Attention Layers are Secretly Long Document Retrievers
David Jiahao Fu, Lam Thanh Do, Jiayu Li +1
Retrieval augmented generation (RAG) has been widely adopted to help Large Language Models (LLMs) to process tasks involving long documents. However, existing retrieval models are…
IRB: Automated Generation of Robust Factuality Benchmarks
Lam Thanh Do, Bhagyashree Taleka, Hozaifa Ammar Bhutta +3
Static benchmarks for RAG systems often suffer from rapid saturation and require significant manual effort to maintain robustness. To address this, we present IRB, a framework for…
CASPER: Concept-integrated Sparse Representation for Scientific Retrieval
Lam Thanh Do, Linh Van Nguyen, Jiayu Li +2
Identifying relevant research concepts is crucial for effective scientific search. However, primary sparse retrieval methods often lack concept-aware representations. To address th…
Writing Like the Best: Exemplar-Based Expository Text Generation
Yuxiang Liu, Kevin Chen-Chuan Chang
We introduce the Exemplar-Based Expository Text Generation task, aiming to generate an expository text on a new topic using an exemplar on a similar topic. Current methods fall sho…
Investigating Instruction Tuning Large Language Models on Graphs
Kerui Zhu, Bo-Wei Huang, Bowen Jin +5
Inspired by the recent advancements of Large Language Models (LLMs) in NLP tasks, there's growing interest in applying LLMs to graph-related tasks. This study delves into the capab…
GPT-Fathom: Benchmarking Large Language Models to Decipher the Evolutionary Path towards GPT-4 and Beyond
Shen Zheng, Yuyu Zhang, Yijie Zhu +4
With the rapid advancement of large language models (LLMs), there is a pressing need for a comprehensive evaluation suite to assess their capabilities and limitations. Existing LLM…