12 citations · 54 across the 20 of their papers we have counts for
6 papers · 1 filter
Speculative RAG: Enhancing Retrieval Augmented Generation through Drafting
Zilong Wang, Zifeng Wang, Long Le +9
Retrieval augmented generation (RAG) combines the generative abilities of large language models (LLMs) with external knowledge sources to provide more accurate and up-to-date respo…
MetaIE: Distilling a Meta Model from LLM for All Kinds of Information Extraction Tasks
Letian Peng, Zilong Wang, Feng Yao +2
Information extraction (IE) is a fundamental area in natural language processing where prompting large language models (LLMs), even with in-context examples, cannot defeat small LM…
DOCMASTER: A Unified Platform for Annotation, Training, & Inference in Document Question-Answering
Alex Nguyen, Zilong Wang, Jingbo Shang +1
The application of natural language processing models to PDF documents is pivotal for various business applications yet the challenge of training models for this purpose persists i…
Answer is All You Need: Instruction-following Text Embedding via Answering the Question
Letian Peng, Yuwei Zhang, Zilong Wang +4
This work aims to build a text embedder that can capture characteristics of texts specified by user instructions. Despite its tremendous potential to deploy user-oriented embedding…
Debug like a Human: A Large Language Model Debugger via Verifying Runtime Execution Step-by-step
Li Zhong, Zilong Wang, Jingbo Shang
Large language models (LLMs) are leading significant progress in code generation. Beyond one-pass code generation, recent works further integrate unit tests and program verifiers i…
Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding
Zilong Wang, Hao Zhang, Chun-Liang Li +8
Table-based reasoning with large language models (LLMs) is a promising direction to tackle many table understanding tasks, such as table-based question answering and fact verificat…