most citedMust Read: A Comprehensive Survey of Computational Persuasion

4 citations · 5 across the 15 of their papers we have counts for

collaborators

16 papers

cs.AI2026

Evaluating the Hidden Costs of Personalization in Large Language Models

Yumeng Wang, Yuchen Wu, Cheng Qian +6

While Large language models (LLMs) incorporate user personalization signals to improve usability and helpfulness, they increasingly shift from providing balanced, informative respo…

cs.RO2026

Generalizable VLA Finetuning via Representation Anchoring and Language-Action Alignment

Dwip Dalal, Shivansh Patel, Chahit Jain +7

Finetuning a pretrained vision-language model (VLM) on robot demonstrations via behavior cloning (BC) has become the standard recipe for vision-language-action (VLA) policies. Howe…

cs.AI2026

Securing Multimodal AI through Internal Information Decomposition

Jehyeok Yeon, Hyeonjeong Ha, Qiusi Zhan +1

Multimodal large language models introduce attack surfaces absent in unimodal systems: adversaries can distribute malicious intent across modalities to evade unimodal safeguards. T…

cs.CV2026

Trimming the Long-Tail of Visual World Modeling Evaluation

Bingxuan Li, Yining Hong, Cheng Qian +6

Physical interactions follow a long-tailed distribution: a set of common and regular interactions dominates human experience and visual data, while a broad spectrum of rare and irr…

cs.AI2026

Advancing Creative Physical Intelligence in Large Multimodal Models

Cheng Qian, Hyeonjeong Ha, Jiayu Liu +10

Large multimodal models (LMMs) have rapidly advanced in perception and reasoning; however, it remains unclear whether these capabilities generalize to discovering visually grounded…

cs.CL2026

MemGuard: Preventing Memory Contamination in Long-Term Memory-Augmented Large Language Models

Hyeonjeong Ha, Jeonghwan Kim, Cheng Qian +7

Memory-augmented large language models extend reasoning beyond a fixed context window by maintaining long-term memory across interactions. However, existing memory systems often co…