activity
20242026
most citedDecAlign: Hierarchical Cross-Modal Alignment for Decoupled Multimodal Representation Learning

5 citations · 10 across the 14 of their papers we have counts for

collaborators

14 papers

cs.AI2026

Beyond Top- Skill Retrieval: Diversity-Aware Skill Routing for LLM Agents

Wang Wei, Tiankai Yang, Samyadeep Basu +7

Large language model (LLM) agents increasingly rely on external skills, but routing user requests over large skill registries is difficult because many skills are functionally redu…

cs.AI2026

Personalized Auto-Research: Towards a True AI Co-Scientist

Bo Ni, Franck Dernoncourt, Hongjie Chen +5

AI co-scientists that generate hypotheses, retrieve related work, design experiments, execute code, and draft full papers are beginning to change how research is carried out. Despi…

cs.CV2026

JigShape: Evaluating Visual-Geometric Reasoning in VLMs through Jigsaw Puzzles

Shawn Li, Wei Yang, Jike Zhong +11

Jigsaw puzzle solving requires jointly reasoning about visual content and geometric constraints, yet existing benchmarks use rectangular cuts that create ambiguous ground truth in…

cs.CL2026

A Survey on LLM-based Conversational User Simulation

Bo Ni, Leyao Wang, Yu Wang +27

User simulation has long played a vital role in computer science due to its potential to support a wide range of applications. Language, as the primary medium of human communicatio…

cs.CV2026

Agent Banana: High-Fidelity Image Editing with Agentic Thinking and Tooling

Ruijie Ye, Jiayi Zhang, Zhuoxin Liu +10

We study instruction-based image editing under professional workflows and identify three persistent challenges: (i) editors often over-edit, modifying content beyond the user's int…

cs.CV2026

Human-Aligned MLLM Judges for Fine-Grained Image Editing Evaluation: A Benchmark, Framework, and Analysis

Runzhou Liu, Hailey Weingord, Sejal Mittal +18

Evaluating image editing models remains challenging due to the coarse granularity and limited interpretability of traditional metrics, which often fail to capture aspects important…