3 citations · 8 across the 17 of their papers we have counts for
7 papers · 1 filter
Evaluating Large Language Models in Scientific Discovery
Zhangde Song, Jieyu Lu, Yuanqi Du +53
Large language models (LLMs) are increasingly applied to scientific research, yet prevailing science benchmarks probe decontextualized knowledge and overlook the iterative reasonin…
BudgetLeak: Membership Inference Attacks on RAG Systems via the Generation Budget Side Channel
Hao Li, Jiajun He, Guangshuo Wang +3
Retrieval-Augmented Generation (RAG) enhances large language models by integrating external knowledge, but reliance on proprietary or sensitive corpora poses various data risks, in…
M4SER: Multimodal, Multirepresentation, Multitask, and Multistrategy Learning for Speech Emotion Recognition
Jiajun He, Xiaohan Shi, Cheng-Hung Hu +3
Multimodal speech emotion recognition (SER) has emerged as pivotal for improving human-machine interaction. Researchers are increasingly leveraging both speech and textual informat…
PARCO: Phoneme-Augmented Robust Contextual ASR via Contrastive Entity Disambiguation
Jiajun He, Naoki Sawada, Koichi Miyazaki +1
Automatic speech recognition (ASR) systems struggle with domain-specific named entities, especially homophones. Contextual ASR improves recognition but often fails to capture fine-…
GIA-MIC: Multimodal Emotion Recognition with Gated Interactive Attention and Modality-Invariant Learning Constraints
Jiajun He, Jinyi Mi, Tomoki Toda
Multimodal emotion recognition (MER) extracts emotions from multimodal data, including visual, speech, and text inputs, playing a key role in human-computer interaction. Attention-…
CMT-LLM: Contextual Multi-Talker ASR Utilizing Large Language Models
Jiajun He, Naoki Sawada, Koichi Miyazaki +1
In real-world applications, automatic speech recognition (ASR) systems must handle overlapping speech from multiple speakers and recognize rare words like technical terms. Traditio…
PMF-CEC: Phoneme-augmented Multimodal Fusion for Context-aware ASR Error Correction with Error-specific Selective Decoding
Jiajun He, Tomoki Toda
End-to-end automatic speech recognition (ASR) models often struggle to accurately recognize rare words. Previously, we introduced an ASR postprocessing method called error detectio…