29 citations · 113 across the 17 of their papers we have counts for
5 papers · 1 filter
CodeJudgeBench: Benchmarking LLM-as-a-Judge for Coding Tasks
Hongchao Jiang, Yiming Chen, Yushi Cao +2
Large Language Models (LLMs) have significantly advanced the state-of-the-art in various coding tasks. Beyond directly answering user queries, LLMs can also serve as judges, assess…
Representation Learning of Structured Data for Medical Foundation Models
Vijay Prakash Dwivedi, Viktor Schlegel, Andy T. Liu +6
Large Language Models (LLMs) have demonstrated remarkable performance across various domains, including healthcare. However, their ability to effectively represent structured non-t…
VoiceBench: Benchmarking LLM-Based Voice Assistants
Yiming Chen, Xianghu Yue, Chen Zhang +3
Building on the success of large language models (LLMs), recent advancements such as GPT-4o have enabled real-time speech interactions through LLM-based voice assistants, offering…
uMedSum: A Unified Framework for Advancing Medical Abstractive Summarization
Aishik Nagar, Yutong Liu, Andy T. Liu +6
Medical abstractive summarization faces the challenge of balancing faithfulness and informativeness. Current methods often sacrifice key information for faithfulness or introduce c…
Unveiling the Achilles' Heel of NLG Evaluators: A Unified Adversarial Framework Driven by Large Language Models
Yiming Chen, Chen Zhang, Danqing Luo +3
The automatic evaluation of natural language generation (NLG) systems presents a long-lasting challenge. Recent studies have highlighted various neural metrics that align well with…