53 citations · 120 across the 25 of their papers we have counts for
32 papers
FlowTool: Controlling Tool Parameter in Image Retouching via Flow Matching
Thanh-Long V. Le, Steven Walton, Seunghyun Yoon +4
Tool-based image editing (image retouching) is commonly formulated with autoregressive multimodal large language models (MLLMs) that sequentially generate reasoning, tool selection…
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…
When Attention Closes: How LLMs Lose the Thread in Multi-Turn Interaction
Vardhan Dongre, Joseph Hsieh, Viet Dac Lai +3
Large language models can follow complex instructions in a single turn, yet over long multi-turn interactions they often lose the thread of instructions, persona, and rules. This d…
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…
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…
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 intention for realistic applications such as Augmented Rea…
Drift No More? Context Equilibria in Multi-Turn LLM Interactions
Vardhan Dongre, Ryan A. Rossi, Viet Dac Lai +3
Large Language Models (LLMs) excel at single-turn tasks such as instruction following and summarization, yet real-world deployments require sustained multi-turn interactions where…
GUI-AIMA: Aligning Intrinsic Multimodal Attention with a Context Anchor for GUI Grounding
Shijie Zhou, Viet Dac Lai, Hao Tan +4
Graphical user interface (GUI) grounding is a key capability for computer-use agents, mapping natural-language instructions to actionable regions on the screen. Existing Multimodal…
A Survey on Long-Video Storytelling Generation: Architectures, Consistency, and Cinematic Quality
Mohamed Elmoghany, Ryan Rossi, Seunghyun Yoon +26
Despite the significant progress that has been made in video generative models, existing state-of-the-art methods can only produce videos lasting 5-16 seconds, often labeled "long-…
FIFA: Unified Faithfulness Evaluation Framework for Text-to-Video and Video-to-Text Generation
Liqiang Jing, Viet Lai, Seunghyun Yoon +2
Video Multimodal Large Language Models (VideoMLLMs) have achieved remarkable progress in both Video-to-Text and Text-to-Video tasks. However, they often suffer fro hallucinations,…
Lizard: An Efficient Linearization Framework for Large Language Models
Chien Van Nguyen, Huy Nguyen, Ruiyi Zhang +10
We propose Lizard, a linearization framework that transforms pretrained Transformer-based Large Language Models (LLMs) into subquadratic architectures. Transformers faces severe co…
Offline RL by Reward-Weighted Fine-Tuning for Conversation Optimization
Subhojyoti Mukherjee, Viet Dac Lai, Raghavendra Addanki +6
Offline reinforcement learning (RL) is a variant of RL where the policy is learned from a previously collected dataset of trajectories and rewards. In our work, we propose a practi…
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…
OWLViz: An Open-World Benchmark for Visual Question Answering
Thuy Nguyen, Dang Nguyen, Hoang Nguyen +3
We present a challenging benchmark for the Open WorLd VISual question answering (OWLViz) task. OWLViz presents concise, unambiguous queries that require integrating multiple capabi…
LUSIFER: Language Universal Space Integration for Enhanced Multilingual Embeddings with Large Language Models
Hieu Man, Nghia Trung Ngo, Viet Dac Lai +3
Recent advancements in large language models (LLMs) based embedding models have established new state-of-the-art benchmarks for text embedding tasks, particularly in dense vector-b…
GUI Agents: A Survey
Dang Nguyen, Jian Chen, Yu Wang +27
Graphical User Interface (GUI) agents, powered by Large Foundation Models, have emerged as a transformative approach to automating human-computer interaction. These agents autonomo…
SlimLM: An Efficient Small Language Model for On-Device Document Assistance
Thang M. Pham, Phat T. Nguyen, Seunghyun Yoon +3
While small language models (SLMs) show promises for mobile deployment, their real-world performance and applications on smartphones remains underexplored. We present SlimLM, a ser…
DynaSaur: Large Language Agents Beyond Predefined Actions
Dang Nguyen, Viet Dac Lai, Seunghyun Yoon +9
Existing LLM agent systems typically select actions from a fixed and predefined set at every step. While this approach is effective in closed, narrowly scoped environments, it pres…
Taipan: Efficient and Expressive State Space Language Models with Selective Attention
Chien Van Nguyen, Huy Huu Nguyen, Thang M. Pham +8
Efficient long-context language modeling remains a significant challenge in Natural Language Processing (NLP). While Transformers dominate language tasks, they struggle with long s…
CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages
Thuat Nguyen, Chien Van Nguyen, Viet Dac Lai +5
The driving factors behind the development of large language models (LLMs) with impressive learning capabilities are their colossal model sizes and extensive training datasets. Alo…
Okapi: Instruction-tuned Large Language Models in Multiple Languages with Reinforcement Learning from Human Feedback
Viet Dac Lai, Chien Van Nguyen, Nghia Trung Ngo +4
A key technology for the development of large language models (LLMs) involves instruction tuning that helps align the models' responses with human expectations to realize impressiv…
ChatGPT Beyond English: Towards a Comprehensive Evaluation of Large Language Models in Multilingual Learning
Viet Dac Lai, Nghia Trung Ngo, Amir Pouran Ben Veyseh +4
Over the last few years, large language models (LLMs) have emerged as the most important breakthroughs in natural language processing (NLP) that fundamentally transform research an…
Event Extraction: A Survey
Viet Dac Lai
Extracting the reported events from text is one of the key research themes in natural language processing. This process includes several tasks such as event detection, argument ext…
Symlink: A New Dataset for Scientific Symbol-Description Linking
Viet Dac Lai, Amir Pouran Ben Veyseh, Franck Dernoncourt +1
Mathematical symbols and descriptions appear in various forms across document section boundaries without explicit markup. In this paper, we present a new large-scale dataset that e…