10 papers
HarmVideoBench: Benchmarking Harmful Video Understanding in Large Multimodal Models
Jiajun Wu, Haoyu Kang, Yining Sun +13
Large vision-language models (LVLMs) have recently shown immense potential in automated content moderation, sparking growing interest in developing harmful-video benchmarks. Howeve…
How Reliable Is Your Jailbreak Judge? Calibration and Adversarial Robustness of Automated ASR Scoring
Yang Gao
Almost every paper on LLM jailbreaks and prompt injection reports an attack-success rate (ASR), and that number is assigned not by people but by an automated judge: either a safety…
Efficient Multimodal Clinical Question Answering for Pulmonary Embolism Risk Assessment
Xiangyuan Xue, Yang Yu, Yan Gao +5
Pulmonary embolism (PE) is a high risk cardiopulmonary condition whose management requires both timely diagnosis and reliable assessment of future clinical risk. Because PE care ro…
HoRD: Robust Humanoid Control via History-Conditioned Reinforcement Learning and Online Distillation
Puyue Wang, Jiawei Hu, Yan Gao +7
Humanoid robots can suffer significant performance drops under small changes in dynamics, task specifications, or environment setup. We propose HoRD, a two-stage learning framework…
Edge-Cloud Collaborative Speech Emotion Captioning via Token-Level Speculative Decoding in Audio-Language Models
Xiangyuan Xue, Jiajun Lu, Yan Gao +3
Speech Emotion Captioning (SEC) leverages large audio-language models to generate rich, context-aware affective descriptions from speech. However, real-world deployment remains cha…
Aligning Large Language Models with Searcher Preferences
Wei Wu, Peilun Zhou, Liyi Chen +6
The paradigm shift from item-centric ranking to answer-centric synthesis is redefining the role of search engines. While recent industrial progress has applied generative technique…
Rethinking Perplexity: Revealing the Impact of Input Length on Perplexity Evaluation in LLMs
Letian Cheng, Junyan Wang, Yan Gao +3
Perplexity is a widely adopted metric for assessing the predictive quality of large language models (LLMs) and often serves as a reference metric for downstream evaluations. Howeve…
Decoding Ambiguous Emotions with Test-Time Scaling in Audio-Language Models
Hong Jia, Weibin Li, Jingyao Wu +6
Emotion recognition from human speech is a critical enabler for socially aware conversational AI. However, while most prior work frames emotion recognition as a categorical classif…
FlowerTune: A Cross-Domain Benchmark for Federated Fine-Tuning of Large Language Models
Yan Gao, Massimo Roberto Scamarcia, Javier Fernandez-Marques +18
Large Language Models (LLMs) have achieved state-of-the-art results across diverse domains, yet their development remains reliant on vast amounts of publicly available data, raisin…
Scaling Auditory Cognition via Test-Time Compute in Audio Language Models
Ting Dang, Yan Gao, Hong Jia
Large language models (LLMs) have shown exceptional versatility in natural language processing, prompting recent efforts to extend their multimodal capabilities to speech processin…