1.3k citations · 2.6k across the 24 of their papers we have counts for
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Disco-Bench: A Discourse-Aware Evaluation Benchmark for Language Modelling
Longyue Wang, Zefeng Du, Donghuai Liu +7
Modeling discourse -- the linguistic phenomena that go beyond individual sentences, is a fundamental yet challenging aspect of natural language processing (NLP). However, existing…
Speech-to-Text Adapter and Speech-to-Entity Retriever Augmented LLMs for Speech Understanding
Mingqiu Wang, Izhak Shafran, Hagen Soltau +4
Large Language Models (LLMs) have been applied in the speech domain, often incurring a performance drop due to misaligned between speech and language representations. To bridge thi…
Towards Understanding What Code Language Models Learned
Toufique Ahmed, Dian Yu, Chengxuan Huang +3
Pre-trained language models are effective in a variety of natural language tasks, but it has been argued their capabilities fall short of fully learning meaning or understanding la…
Tree of Thoughts: Deliberate Problem Solving with Large Language Models
Shunyu Yao, Dian Yu, Jeffrey Zhao +4
Language models are increasingly being deployed for general problem solving across a wide range of tasks, but are still confined to token-level, left-to-right decision-making proce…
Document-Level Machine Translation with Large Language Models
Longyue Wang, Chenyang Lyu, Tianbo Ji +4
Large language models (LLMs) such as ChatGPT can produce coherent, cohesive, relevant, and fluent answers for various natural language processing (NLP) tasks. Taking document-level…