collaborators

18 papers

cs.CV2026

SliderEdit++: Improved Slider Trajectories in Instruction-Based Image Editing

Arman Zarei, Sayan Nag, Bryan Wang +5

Slider-based control aims to give users continuous, fine-grained control over the intensity of individual edits in instruction-based image editing. However, existing approaches fai…

cs.CV2026

Personalized Image Generation with Reasoning and Reflection

Bo Ni, Ngoc N. Tran, Qinwen Ge +10

Personalized image generation has remained narrowly focused on conditional synthesis from curated visual exemplars, rather than capturing who a user is. In practice, however, a use…

cs.CL2026

Prompt2Skill: Unsupervised Skill Optimization From Natural Language Instructions

Bo Ni, Li Li, Ryan A. Rossi +2

Skills are external artifacts that Large Language Models (LLMs) consume at inference time to improve their performance on specialized domains by incorporating relevant procedural a…

cs.CV2026

Joint and Cross-Modal Video-Audio Generation and Editing: A Unified Formulation and Design Taxonomy

Abhinav Sharma, Sai Karthik Navuluru, Wang Wei +21

Video and audio are perceived together, yet most generative models treat them in isolation. We examine methods that model the two modalities jointly, generate one from the other, o…

cs.CL2026

DISCO: Distributed Long Context Scaling with Grounding-Reasoning Disaggregation

Guanzheng Chen, Viet Dac Lai, Subhojyoti Mukherjee +5

While Large Language Models (LLMs) advertise million-token context windows, reasoning quality often collapses as inputs grow -- a phenomenon termed context rot. This failure stems…

cs.CV2026

A Glance Is All You Need: Single-Pass Fine-Grained Image Captioning with SimLoss

Suryaansh Jain, Rahasya Barkur, Vishal G +8

An image may be worth a thousand words, but most captioning models describe it in only a few. Modern vision-language models produce fluent high-level captions, yet routinely miss t…

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

ViT-AdaLA: Adapting Vision Transformers with Linear Attention

Yifan Li, Seunghyun Yoon, Viet Dac Lai +4

Vision Transformers (ViTs) based vision foundation models (VFMs) have achieved remarkable performance across diverse vision tasks, but suffer from quadratic complexity that limits…

cs.CL2026

Can Large Language Models Keep Up? Benchmarking Online Adaptation to Continual Knowledge Streams

Jiyeon Kim, Hyunji Lee, Dylan Zhou +6

LLMs operating in dynamic real-world contexts often encounter knowledge that evolves continuously or emerges incrementally. To remain accurate and effective, models must adapt to n…

cs.LG2026

Agentic Planning with Reasoning for Image Styling via Offline RL

Subhojyoti Mukherjee, Stefano Petrangeli, Branislav Kveton +3

Direct prompt-based editing often fails on complex transformations because vague and subjective prompts often require nuanced understanding of what should be changed in the image.…

cs.CV2026

InfinityStory: Unlimited Video Generation with World Consistency and Character-Aware Shot Transitions

Mohamed Elmoghany, Liangbing Zhao, Xiaoqian Shen +27

Generating long-form storytelling videos with consistent visual narratives remains a significant challenge in video synthesis. We present a novel framework, dataset, and a model th…

cs.CV2025

StreamGaze: Gaze-Guided Temporal Reasoning and Proactive Understanding in Streaming Videos

Daeun Lee, Subhojyoti Mukherjee, Branislav Kveton +6

Streaming video understanding requires models not only to process temporally incoming frames, but also to anticipate user intent for realistic applications such as Augmented Realit…

cs.CL2025

Steering MoE LLMs via Expert (De)Activation

Mohsen Fayyaz, Ali Modarressi, Hanieh Deilamsalehy +5

Mixture-of-Experts (MoE) in Large Language Models (LLMs) routes each token through a subset of specialized Feed-Forward Networks (FFN), known as experts. We present SteerMoE, a fra…

cs.CV2025

MS4UI: A Dataset for Multi-modal Summarization of User Interface Instructional Videos

Yuan Zang, Hao Tan, Seunghyun Yoon +5

We study multi-modal summarization for instructional videos, whose goal is to provide users an efficient way to learn skills in the form of text instructions and key video frames.…

cs.CL2025

Instruction Tuning with and without Context: Behavioral Shifts and Downstream Impact

Hyunji Lee, Seunghyun Yoon, Yunjae Won +7

Instruction tuning is a widely used approach to improve the instruction-following ability of large language models (LLMs). Instruction-tuning datasets typically include a mixture o…

cs.CV2025

Understanding Generative AI Capabilities in Everyday Image Editing Tasks

Mohammad Reza Taesiri, Brandon Collins, Logan Bolton +4

Generative AI (GenAI) holds significant promise for automating everyday image editing tasks, especially following the recent release of GPT-4o on March 25, 2025. However, what subj…

cs.CL2025

CORG: Generating Answers from Complex, Interrelated Contexts

Hyunji Lee, Franck Dernoncourt, Trung Bui +1

In a real-world corpus, knowledge frequently recurs across documents but often contains inconsistencies due to ambiguous naming, outdated information, or errors, leading to complex…