activity
20202023
most citedMacaw-LLM: Multi-Modal Language Modeling with Image, Audio, Video, and Text Integration

27 citations · 41 across the 6 of their papers we have counts for

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Showing cs.CLShow all

6 papers · 1 filter

cs.CL202327 cited

Macaw-LLM: Multi-Modal Language Modeling with Image, Audio, Video, and Text Integration

Chenyang Lyu, Minghao Wu, Longyue Wang +5

Although instruction-tuned large language models (LLMs) have exhibited remarkable capabilities across various NLP tasks, their effectiveness on other data modalities beyond text ha…

cs.CL202212 cited

QAScore -- An Unsupervised Unreferenced Metric for the Question Generation Evaluation

Tianbo Ji, Chenyang Lyu, Gareth Jones +2

Question Generation (QG) aims to automate the task of composing questions for a passage with a set of chosen answers found within the passage. In recent years, the introduction of…

cs.CL2022

Extending the Scope of Out-of-Domain: Examining QA models in multiple subdomains

Chenyang Lyu, Jennifer Foster, Yvette Graham

Past works that investigate out-of-domain performance of QA systems have mainly focused on general domains (e.g. news domain, wikipedia domain), underestimating the importance of s…

cs.CL20222 cited

Achieving Reliable Human Assessment of Open-Domain Dialogue Systems

Tianbo Ji, Yvette Graham, Gareth J. F. Jones +2

Evaluation of open-domain dialogue systems is highly challenging and development of better techniques is highlighted time and again as desperately needed. Despite substantial effor…

cs.CL2021

Improving Unsupervised Question Answering via Summarization-Informed Question Generation

Chenyang Lyu, Lifeng Shang, Yvette Graham +3

Question Generation (QG) is the task of generating a plausible question for a given <passage, answer> pair. Template-based QG uses linguistically-informed heuristics to transform d…

cs.CL2020

Improving Document-Level Sentiment Analysis with User and Product Context

Chenyang Lyu, Jennifer Foster, Yvette Graham

Past work that improves document-level sentiment analysis by encoding user and product information has been limited to considering only the text of the current review. We investiga…