127 citations · 168 across the 38 of their papers we have counts for
15 papers · 1 filter
VideoChat-M1: Collaborative Policy Planning for Video Understanding via Multi-Agent Reinforcement Learning
Boyu Chen, Zikang Wang, Zhengrong Yue +9
By leveraging tool-augmented Multimodal Large Language Models (MLLMs), multi-agent frameworks are driving progress in video understanding. However, most of them adopt static and no…
GTA: Supervised-Guided Reinforcement Learning for Text Classification with Large Language Models
Min Zeng, Jingfei Sun, Xueyou Luo +4
In natural language processing tasks, pure reinforcement learning (RL) fine-tuning methods often suffer from inefficient exploration and slow convergence; while supervised fine-tun…
EdgeInfinite-Instruct: Bridging SFT-Based Optimization and NPU-Level Efficiency for Edge Devices
Jiyu Chen, Poh Seng Lim, Shuang Peng +12
Deploying Transformer-based large language models (LLMs) on resource-constrained edge devices for long-sequence tasks remains challenging due to the quadratic time complexity of se…
LENS: Learning to Segment Anything with Unified Reinforced Reasoning
Lianghui Zhu, Bin Ouyang, Yuxuan Zhang +8
Text-prompted image segmentation enables fine-grained visual understanding and is critical for applications such as human-computer interaction and robotics. However, existing super…
BlueLM-2.5-3B Technical Report
Baojiao Xiong, Boheng Chen, Chengzhi Wang +58
We present BlueLM-2.5-3B, a compact and unified dense Multimodal Large Language Model (MLLM) designed for efficient edge-device deployment, offering strong general-purpose and reas…
UI-Genie: A Self-Improving Approach for Iteratively Boosting MLLM-based Mobile GUI Agents
Han Xiao, Guozhi Wang, Yuxiang Chai +12
In this paper, we introduce UI-Genie, a self-improving framework addressing two key challenges in GUI agents: verification of trajectory outcome is challenging and high-quality tra…
Adaptive Markup Language Generation for Contextually-Grounded Visual Document Understanding
Han Xiao, Yina Xie, Guanxin Tan +12
Visual Document Understanding has become essential with the increase of text-rich visual content. This field poses significant challenges due to the need for effective integration…
PixelHacker: Image Inpainting with Structural and Semantic Consistency
Ziyang Xu, Kangsheng Duan, Xiaolei Shen +5
Image inpainting is a fundamental research area between image editing and image generation. Recent state-of-the-art (SOTA) methods have explored novel attention mechanisms, lightwe…
EdgeInfinite: A Memory-Efficient Infinite-Context Transformer for Edge Devices
Jiyu Chen, Shuang Peng, Daxiong Luo +4
Transformer-based large language models (LLMs) encounter challenges in processing long sequences on edge devices due to the quadratic complexity of attention mechanisms and growing…
GenieBlue: Integrating both Linguistic and Multimodal Capabilities for Large Language Models on Mobile Devices
Xudong Lu, Yinghao Chen, Renshou Wu +10
Recent advancements in Multimodal Large Language Models (MLLMs) have enabled their deployment on mobile devices. However, challenges persist in maintaining strong language capabili…
GroundingSuite: Measuring Complex Multi-Granular Pixel Grounding
Rui Hu, Lianghui Zhu, Yuxuan Zhang +7
Pixel grounding, encompassing tasks such as Referring Expression Segmentation (RES), has garnered considerable attention due to its immense potential for bridging the gap between v…
SmartBench: Is Your LLM Truly a Good Chinese Smartphone Assistant?
Xudong Lu, Haohao Gao, Renshou Wu +4
Large Language Models (LLMs) have become integral to daily life, especially advancing as intelligent assistants through on-device deployment on smartphones. However, existing LLM e…
Predictive Data Selection: The Data That Predicts Is the Data That Teaches
Kashun Shum, Yuzhen Huang, Hongjian Zou +5
Language model pretraining involves training on extensive corpora, where data quality plays a pivotal role. In this work, we aim to directly estimate the contribution of data durin…
Autonomous Deep Agent
Amy Yu, Erik Lebedev, Lincoln Everett +2
This technical brief introduces Deep Agent, an advanced autonomous AI system designed to manage complex multi-phase tasks through a novel hierarchical task management architecture.…
Baichuan-Omni-1.5 Technical Report
Yadong Li, Jun Liu, Tao Zhang +89
We introduce Baichuan-Omni-1.5, an omni-modal model that not only has omni-modal understanding capabilities but also provides end-to-end audio generation capabilities. To achieve f…