1 citations · 1 across the 12 of their papers we have counts for
14 papers
Imprinting: Knowledge Distillation Can Shift Student Behavior
Yu-Chien Tang, An-Zi Yen
Knowledge distillation trains student models on teacher-generated responses to transfer task capability, but those responses may also carry behavioral tendencies of their source. W…
EgoArgus: Benchmarking VLMs as Situational Assistants for Modality-Grounded User Supports
Yu-Chien Tang, Yu-Hsiang Liu, An-Zi Yen
VLMs are increasingly positioned as daily assistants that perceive first-person environments, follow user dialogue, and decide how to help. Existing egocentric benchmarks mainly ev…
VDAR-Router: Adaptive LLMs Routing via Verbalized Query Difficulty Analysis Retrieval
Yu-Chien Tang, Jun-Chen Hung, Wen-Chih Peng +1
Large language models are increasingly used in practical systems, making efficient model selection important for reducing deployment cost. LLM routing has emerged as a practical so…
VISTA: A Controllable Platform for Generating and Auditing Egocentric Assistance Scenarios
Yu-Hsiang Liu, Yu-Chien Tang, An-Zi Yen
Evaluating whether AI agents can proactively assist humans in daily activities, ranging from routine household tasks to urgent safety-critical situations, requires diverse visual d…
Tree-of-Text: A Tree-based Prompting Framework for Table-to-Text Generation in the Sports Domain
Shang-Hsuan Chiang, Tsan-Tsung Yang, An-Zi Yen +1
Generating sports game reports from structured tables is a complex table-to-text task that demands both precise data interpretation and fluent narrative generation. Traditional mod…
ConceptKT: A Benchmark for Concept-Level Deficiency Prediction in Knowledge Tracing
Yu-Chen Kang, Yu-Chien Tang, An-Zi Yen
Knowledge Tracing (KT) is a critical technique for modeling student knowledge to support personalized learning. However, most KT systems focus on binary correctness prediction and…
OI-Bench: An Option Injection Benchmark for Evaluating LLM Susceptibility to Directive Interference
Yow-Fu Liou, Yu-Chien Tang, Yu-Hsiang Liu +1
Benchmarking large language models (LLMs) is critical for understanding their capabilities, limitations, and robustness. In addition to interface artifacts, prior studies have show…
CARPAS: Towards Content-Aware Refinement of Provided Aspects for Summarization in Large Language Models
Yong-En Tian, Yu-Chien Tang, An-Zi Yen +1
Aspect-based summarization has attracted significant attention for its ability to generate more fine-grained and user-aligned summaries. While most existing approaches assume a set…
DaMO: A Data-Efficient Multimodal Orchestrator for Temporal Reasoning with Video LLMs
Bo-Cheng Chiu, Jen-Jee Chen, Yu-Chee Tseng +2
Large Language Models (LLMs) have recently been extended to the video domain, enabling sophisticated video-language understanding. However, existing Video LLMs often exhibit limita…
MathEDU: Feedback Generation on Problem-Solving Processes for Mathematical Learning Support
Wei-Ling Hsu, Yu-Chien Tang, An-Zi Yen
The increasing reliance on Large Language Models (LLMs) across various domains extends to education, where students progressively use generative AI as a tool for learning. While pr…
Stay Hungry, Stay Foolish: On the Extended Reading Articles Generation with LLMs
Yow-Fu Liou, Yu-Chien Tang, An-Zi Yen
The process of creating educational materials is both time-consuming and demanding for educators. This research explores the potential of Large Language Models (LLMs) to streamline…
Template-Based Financial Report Generation in Agentic and Decomposed Information Retrieval
Yong-En Tian, Yu-Chien Tang, Kuang-Da Wang +2
Tailoring structured financial reports from companies' earnings releases is crucial for understanding financial performance and has been widely adopted in real-world analytics. How…
Three Questions Concerning the Use of Large Language Models to Facilitate Mathematics Learning
An-Zi Yen, Wei-Ling Hsu
Due to the remarkable language understanding and generation abilities of large language models (LLMs), their use in educational applications has been explored. However, little work…
RSVP: Customer Intent Detection via Agent Response Contrastive and Generative Pre-Training
Yu-Chien Tang, Wei-Yao Wang, An-Zi Yen +1
The dialogue systems in customer services have been developed with neural models to provide users with precise answers and round-the-clock support in task-oriented conversations by…