7 citations · 20 across the 40 of their papers we have counts for
10 papers · 2 filters
PremiseSQL: Evaluating Premise Critique and Abstention in Text-to-SQL Systems
Shuo Lin, Jinzhe Li, Chenlu Guo +3
Recent advances in large language models (LLMs) have substantially improved Text-to-SQL performance, yet existing NL2SQL systems largely assume that user queries are valid and answ…
CSWBench: Evaluating Context-Sensitive Code-Switching in Creative Writing
Zewen Jiang, Yahan Li, Chenlu Guo +3
Large language models (LLMs) have demonstrated multilingual capabilities across diverse language generation and understanding tasks. Yet effective code-switching requires more than…
TRACESTEER: Trace Driven Activation Steering for Hallucination Mitigation in Diffusion Language Models
Xin Zhang, Yili Wang, Yue Tan +5
Diffusion large language models (dLLMs) have emerged as a promising alternative to autoregressive LLMs, yet remain susceptible to hallucination. Activation steering offers a promis…
What if LLMs Ate Their Words: Causal History Effects in Multi-Turn Interaction
Jinnan Li, Zheren Fu, Yue Wang +3
Multi-turn interaction creates a feedback process in which an LLM's previous responses become context for later behavior. Prior work shows substantial multi-turn degradation and th…
OCR-MetaReasoning Benchmark: Evaluating the Meta-Reasoning Ability of MLLMs in Text-Rich Image Understanding
Gengxu Li, Yuan Wu, Yi Chang
Text-rich image understanding requires multimodal large language models (MLLMs) to organize OCR (Optical Character Recognition)-grounded evidence across words, layout, fields, char…
How Agents Represent Humans: Human-Directed Stereotypes in an Open Agent Social Network
Huangchen Xu, Yuan Wu, Yi Chang
LLM-based agents are increasingly deployed in persistent social environments, where generated claims can be posted, replied to, remembered, and reused. We study human-directed ster…
Thinking vs. NoThinking: Towards Interpreting Reasoning Mechanisms of Large Language Models via Sparse Autoencoders
Bo Cheng, Qiaolin Lu, Yi Chang +1
While Large Language Models (LLMs) employing Chain-of-Thought (CoT) exhibit superior reasoning capabilities, the neural mechanisms distinguishing this explicit Thinking mode from d…
DeMTS: Denoising Trajectories as Multivariate Time Series for Hallucination Detection in Diffusion Language Models
Xin Zhang, Yili Wang, Yue Tan +6
Diffusion large language models (D-LLMs) have emerged as a promising paradigm for text generation. However, similar to autoregressive LLMs, D-LLMs remain vulnerable to hallucinatio…
A Systematic Evaluation of Positional Bias in Multi-Video Summarization with MLLMs
Huangchen Xu, Yuan Wu, Yi Chang
Multimodal Large Language Models (MLLMs) are increasingly used for video understanding, yet their reliability under multi-video inputs remains poorly understood. We study positiona…
VCIFBench: Evaluating Complex Instruction Following for Video Understanding
Huangchen Xu, Yuan Wu, Yi Chang
Multimodal large language models have made rapid progress in video understanding, yet existing benchmarks largely rely on simple prompts and provide limited evidence about whether…