1 citations · 2 across the 16 of their papers we have counts for
18 papers
SCOPE: Semantic Bounded Credit Optimization for Prompt Engineering in Text-to-image Generation
Yufei Jiao, Jinfa Huang, Zeyue Xue +5
Reinforcement learning (RL) enables language models to improve text-to-image (T2I) generation by rewriting prompts for a frozen image generator. Existing methods typically apply a…
Toward Robust In-Context Segmentation via Concept Guidance
Zhigang Chen, Xiawu Zheng, Rongrong Ji
In-context segmentation (ICS) requires a model to segment target regions in a query image using only a few reference images and their corresponding masks, without updating any para…
A2RBench: An Automatic Paradigm for Formally Verifiable Abstract Reasoning Benchmark Generation
Qingchuan Ma, Yuexiao Ma, Yongkang Xie +3
Abstract reasoning ability reflects the intelligence and generalization capacity of LLMs to extract and apply abstract rules. However, accurately measuring this ability remains cha…
ALGOGEN: Tool-Generated Verifiable Traces for Reliable Algorithm Visualization
Kunpeng Liao, Yuexiao Ma, Yisheng Lin +3
Algorithm Visualization (AV) helps students build mental models by animating algorithm execution states. Recent LLM-based systems such as CODE2VIDEO generate AV videos in an end-to…
HEART: Exploiting Head Heterogeneity in Sparse Attention for Video Diffusion
Xuzhe Zheng, Yuexiao Ma, Jing Xu +3
Sparse attention accelerates video diffusion by allowing each attention head to focus on only a small subset of interactions. Existing methods already construct head-specific spars…
ForestPrune: High-ratio Visual Token Compression for Video Multimodal Large Language Models via Spatial-Temporal Forest Modeling
Shaobo Ju, Baiyang Song, Tao Chen +6
Due to the great saving of computation and memory overhead, token compression has become a research hot-spot for MLLMs and achieved remarkable progress in image-language tasks. How…
SpecEyes: Accelerating Agentic Multimodal LLMs via Speculative Perception and Planning
Haoyu Huang, Jinfa Huang, Zhongwei Wan +3
Agentic multimodal large language models (MLLMs) (e.g., OpenAI o3 and Gemini Agentic Vision) achieve remarkable reasoning capabilities through iterative visual tool invocation. How…
Flow caching for autoregressive video generation
Yuexiao Ma, Xuzhe Zheng, Jing Xu +9
Autoregressive models, often built on Transformer architectures, represent a powerful paradigm for generating ultra-long videos by synthesizing content in sequential chunks. Howeve…
Polybasic Speculative Decoding Through a Theoretical Perspective
Ruilin Wang, Huixia Li, Yuexiao Ma +4
Inference latency stands as a critical bottleneck in the large-scale deployment of Large Language Models (LLMs). Speculative decoding methods have recently shown promise in acceler…
Mix-Ecom: Towards Mixed-Type E-Commerce Dialogues with Complex Domain Rules
Chenyu Zhou, Xiaoming Shi, Hui Qiu +6
E-commerce agents contribute greatly to helping users complete their e-commerce needs. To promote further research and application of e-commerce agents, benchmarking frameworks are…
Benchmarking Abstract and Reasoning Abilities Through A Theoretical Perspective
Qingchuan Ma, Yuhang Wu, Xiawu Zheng +1
In this paper, we aim to establish a simple, effective, and theoretically grounded benchmark for rigorously probing abstract reasoning in Large Language Models (LLMs). To achieve t…
QuoTA: Query-oriented Token Assignment via CoT Query Decouple for Long Video Comprehension
Yongdong Luo, Wang Chen, Xiawu Zheng +8
Recent advances in long video understanding typically mitigate visual redundancy through visual token pruning based on attention distribution. However, while existing methods emplo…
Video-RAG: Visually-aligned Retrieval-Augmented Long Video Comprehension
Yongdong Luo, Xiawu Zheng, Guilin Li +8
Existing large video-language models (LVLMs) struggle to comprehend long videos correctly due to limited context. To address this problem, fine-tuning long-context LVLMs and employ…
GraCo: Granularity-Controllable Interactive Segmentation
Yian Zhao, Kehan Li, Zesen Cheng +6
Interactive Segmentation (IS) segments specific objects or parts in the image according to user input. Current IS pipelines fall into two categories: single-granularity output and…
Rethinking 3D Dense Caption and Visual Grounding in A Unified Framework through Prompt-based Localization
Yongdong Luo, Haojia Lin, Xiawu Zheng +6
3D Visual Grounding (3DVG) and 3D Dense Captioning (3DDC) are two crucial tasks in various 3D applications, which require both shared and complementary information in localization…
AffineQuant: Affine Transformation Quantization for Large Language Models
Yuexiao Ma, Huixia Li, Xiawu Zheng +6
The significant resource requirements associated with Large-scale Language Models (LLMs) have generated considerable interest in the development of techniques aimed at compressing…
EBFT: Effective and Block-Wise Fine-Tuning for Sparse LLMs
Song Guo, Fan Wu, Lei Zhang +5
Existing methods for fine-tuning sparse LLMs often suffer from resource-intensive requirements and high retraining costs. Additionally, many fine-tuning methods often rely on appro…
Instance Brownian Bridge as Texts for Open-vocabulary Video Instance Segmentation
Zesen Cheng, Kehan Li, Hao Li +5
Temporally locating objects with arbitrary class texts is the primary pursuit of open-vocabulary Video Instance Segmentation (VIS). Because of the insufficient vocabulary of video…