13 citations · 13 across the 7 of their papers we have counts for
7 papers
EmoS: A Theory-Grounded Framework for Evaluating and Aligning Emotional Intelligence in Spoken Language Models
Junyu Wang, Siyuan Zhang, Peiyuan Jiang +11
Despite significant advances in instruction-following and auditory comprehension, the evaluation of Emotional Intelligence (EI) in Spoken Language Models (SLMs) remains confined to…
EChO-Agent: Evidence Chain Orchestration Agent for Audio Reasoning
Siyuan Zhang, Jian Zong, Junyu Wang +7
While LALMs show promise on audio question answering, they fail to focus on question-relevant segments of audio and provide a clear, checkable reasoning process when dealing with c…
How Notations Evolve: A Historical Analysis with Implications for Supporting User-Defined Abstractions
Jingyue Zhang, J. D. Zamfirescu-Pereira, Elena L. Glassman +2
Traditional human-computer interaction takes place through formally-specified systems like structured UIs and programming languages. Recent AI systems promise a new set of informal…
Language Model Agents Under Attack: A Cross Model-Benchmark of Profit-Seeking Behaviors in Customer Service
Jingyu Zhang
Customer-service LLM agents increasingly make policy-bound decisions (refunds, rebooking, billing disputes), but the same ``helpful'' interaction style can be exploited: a small fr…
SoK: Systematizing LLM Prompt Security: Taxonomies, Datasets, and Unified Evaluation of Attacks and Defenses
Hanbin Hong, Shuang Wu, Shuya Feng +6
Prompt-security claims for large language models (LLMs) are often compared as properties of individual attacks or defenses, although measured harmfulness depends on the target mode…
Jailbreak Distillation: Renewable Safety Benchmarking
Jingyu Zhang, Ahmed Elgohary, Xiawei Wang +5
Large language models (LLMs) are rapidly deployed in critical applications, raising urgent needs for robust safety benchmarking. We propose Jailbreak Distillation (JBDistill), a no…
ChainBuddy: An AI Agent System for Generating LLM Pipelines
Jingyue Zhang, Ian Arawjo
As large language models (LLMs) advance, their potential applications have grown significantly. However, it remains difficult to evaluate LLM behavior on user-defined tasks and cra…