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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…