most citedLarge Language Model Alignment: A Survey

36 citations · 42 across the 5 of their papers we have counts for

collaborators

5 papers

cs.AI20241 cited

Sibyl: Simple yet Effective Agent Framework for Complex Real-world Reasoning

Yulong Wang, Tianhao Shen, Lifeng Liu +1

Existing agents based on large language models (LLMs) demonstrate robust problem-solving capabilities by integrating LLMs' inherent knowledge, strong in-context learning and zero-s…

cs.AI20241 cited

GIEBench: Towards Holistic Evaluation of Group Identity-based Empathy for Large Language Models

Leyan Wang, Yonggang Jin, Tianhao Shen +9

As large language models (LLMs) continue to develop and gain widespread application, the ability of LLMs to exhibit empathy towards diverse group identities and understand their pe…

cs.CL2024

Benchmarks Underestimate the Readiness of Multi-lingual Dialogue Agents

Andrew H. Lee, Sina J. Semnani, Galo Castillo-López +16

Creating multilingual task-oriented dialogue (TOD) agents is challenging due to the high cost of training data acquisition. Following the research trend of improving training data…

cs.SD20244 cited

ChatMusician: Understanding and Generating Music Intrinsically with LLM

Ruibin Yuan, Hanfeng Lin, Yi Wang +32

While Large Language Models (LLMs) demonstrate impressive capabilities in text generation, we find that their ability has yet to be generalized to music, humanity's creative langua…

cs.CL202336 cited

Large Language Model Alignment: A Survey

Tianhao Shen, Renren Jin, Yufei Huang +6

Recent years have witnessed remarkable progress made in large language models (LLMs). Such advancements, while garnering significant attention, have concurrently elicited various c…