activity
20192026
most citedHead-to-Tail: How Knowledgeable are Large Language Models (LLMs)? A.K.A. Will LLMs Replace Knowledge Graphs?

13 citations · 40 across the 6 of their papers we have counts for

collaborators

7 papers

cs.CL2026

Muse Glimmer 30B: An On-Device Agentic Model

Arash Ebrahim Abtahizadeh, Muna Aghamelu, Adil Ahmed +327

We introduce Muse Glimmer, an open-source 30B parameter causal language model with perception encoder, purpose-built for autonomous agentic tasks on consumer hardware. Muse Glimmer…

cs.CL2024★ 8 cited

CRAG -- Comprehensive RAG Benchmark

Xiao Yang, Kai Sun, Hao Xin +24

Retrieval-Augmented Generation (RAG) has recently emerged as a promising solution to alleviate Large Language Model (LLM)'s deficiency in lack of knowledge. Existing RAG datasets,…

cs.CL2023★ 13 cited

Head-to-Tail: How Knowledgeable are Large Language Models (LLMs)? A.K.A. Will LLMs Replace Knowledge Graphs?

Kai Sun, Yifan Ethan Xu, Hanwen Zha +2

Since the recent prosperity of Large Language Models (LLMs), there have been interleaved discussions regarding how to reduce hallucinations from LLM responses, how to increase the…

cs.CL2023★ 1 cited

Improving Opinion-based Question Answering Systems Through Label Error Detection and Overwrite

Xiao Yang, Ahmed K. Mohamed, Shashank Jain +6

Label error is a ubiquitous problem in annotated data. Large amounts of label error substantially degrades the quality of deep learning models. Existing methods to tackle the label…

cs.CL2020★ 4 cited

Logic2Text: High-Fidelity Natural Language Generation from Logical Forms

Zhiyu Chen, Wenhu Chen, Hanwen Zha +4

Previous works on Natural Language Generation (NLG) from structured data have primarily focused on surface-level descriptions of record sequences. However, for complex structured d…

cs.CL2020★ 12 cited

HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data

Wenhu Chen, Hanwen Zha, Zhiyu Chen +3

Existing question answering datasets focus on dealing with homogeneous information, based either only on text or KB/Table information alone. However, as human knowledge is distribu…

cs.CL2019★ 2 cited

Global Textual Relation Embedding for Relational Understanding

Zhiyu Chen, Hanwen Zha, Honglei Liu +3

Pre-trained embeddings such as word embeddings and sentence embeddings are fundamental tools facilitating a wide range of downstream NLP tasks. In this work, we investigate how to…