1 citations · 2 across the 8 of their papers we have counts for
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Type-Balanced Contextual Learning for Incremental Named Entity Recognition
Duzhen Zhang, Yahan Yu, Xiuyi Chen +2
Incremental Named Entity Recognition (INER) stands as a pivotal task in information extraction, emphasizing the successive identification of new entity types within unstructured te…
Revisiting Anthropomorphic Reflection Markers in Large Language Model Reasoning
Yahan Yu, Noa Nakanishi, Fei Cheng
Large Language Models (LLMs) often produce explicit reflective traces during complex reasoning, accompanied by anthropomorphic markers such as wait, hmm, and alternatively. Althoug…
MedKGent: A Large Language Model Agent Framework for Constructing Temporally Evolving Medical Knowledge Graph
Duzhen Zhang, Zixiao Wang, Zhong-Zhi Li +10
The rapid expansion of medical literature challenges the scalable structuring of domain knowledge. Knowledge Graphs (KGs) offer a solution, yet current construction methods lack ge…
SpeechIQ: Speech-Agentic Intelligence Quotient Across Cognitive Levels in Voice Understanding by Large Language Models
Zhen Wan, Chao-Han Huck Yang, Yahan Yu +8
We introduce Speech-based Intelligence Quotient (SIQ) as a new form of human cognition-inspired evaluation pipeline for voice understanding large language models, LLM Voice, design…
Enhancing Multimodal Continual Instruction Tuning with BranchLoRA
Duzhen Zhang, Yong Ren, Zhong-Zhi Li +5
Multimodal Continual Instruction Tuning (MCIT) aims to finetune Multimodal Large Language Models (MLLMs) to continually align with human intent across sequential tasks. Existing ap…
When Large Language Models Meet Speech: A Survey on Integration Approaches
Zhengdong Yang, Shuichiro Shimizu, Yahan Yu +1
Recent advancements in large language models (LLMs) have spurred interest in expanding their application beyond text-based tasks. A large number of studies have explored integratin…