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Ningning Wang, Xavier Hu, Pai Liu +11 authors
A study on the efficiency-effectiveness trade-off in LLM-driven agent systems identifies optimal agent framework design to reduce costs while maintaining performance.
Zongxia Li, Wenhao Yu, Chengsong Huang +8 authors
Vision-SR1 uses reinforcement learning to enhance visual reasoning in vision-language models by decomposing the process into visual perception and language reasoning stages, improving accuracy and reducing hallucinations.
Yi-Fan Zhang, Xingyu Lu, Shukang Yin +17 authors
Thyme, a novel paradigm, enables MLLMs to autonomously perform image manipulations and computations, enhancing performance in perception and reasoning tasks through a two-stage training strategy and GRPO-ATS algorithm.
Yizhi Li, Qingshui Gu, Zhoufutu Wen +14 authors
TreePO, a self-guided rollout algorithm for sequence generation, reduces computational cost and enhances exploration diversity in reinforcement learning for large language models.
Juyuan Wang, Rongchen Zhao, Wei Wei +5 authors
ComoRAG, an iterative retrieval-based approach, enhances long-context narrative comprehension by dynamically updating memory and generating probing queries, outperforming traditional RAG methods.
Zhiyuan Zeng, Jiashuo Liu, Siyuan Chen +27 authors
FutureX is a dynamic, live benchmark for evaluating LLM agents in future prediction tasks, addressing challenges in real-time updates and data contamination.
Yue Liao, Pengfei Zhou, Siyuan Huang +11 authors
Genie Envisioner integrates policy learning, evaluation, and simulation using a video diffusion model and neural simulator for instruction-driven robotic manipulation.
Mo Yu, Tsz Ting Chung, Chulun Zhou +8 authors
A benchmark called PRELUDE evaluates long-context understanding by assessing the consistency of prequel stories with original books, revealing significant challenges for models compared to humans.
Bingquan Dai, Li Ray Luo, Qihong Tang +9 authors
MeshCoder reconstructs complex 3D objects from point clouds into editable Blender Python scripts, enhancing shape-to-code reconstruction and 3D shape understanding through a multimodal large language model.
David Dinkevich, Matan Levy, Omri Avrahami +2 authors
Story2Board generates expressive storyboards from natural language using a consistency framework that enhances coherence and diversity without fine-tuning.
Dawei Gao, Zitao Li, Yuexiang Xie +20 authors
AgentScope enhances agentic applications by providing flexible tool-based interactions, unified interfaces, and advanced infrastructure based on the ReAct paradigm, supporting efficient and safe development and deployment.
Xinrun Xu, Pi Bu, Ye Wang +7 authors
DeepPHY evaluates Vision Language Models' physical reasoning and control through simulated environments with varying difficulty levels.
Peiyu Wang, Yi Peng, Yimeng Gan +12 authors
Skywork UniPic, a 1.5 billion-parameter autoregressive model, unifies image understanding, text-to-image generation, and image editing with state-of-the-art performance on commodity hardware.
Jinsong Li, Xiaoyi Dong, Yuhang Zang +3 authors
DAEDAL, a novel training-free denoising strategy, enables dynamic length adaptation in Diffusion Large Language Models, improving performance and computational efficiency.
Zhenting Wang, Qi Chang, Hemani Patel +8 authors
MCP-Bench evaluates large language models on complex, multi-step tasks requiring tool use, coordination, and planning across various domains.
Zhaoxi Chen, Tianqi Liu, Long Zhuo +6 authors
4DNeX generates high-quality dynamic 3D scene representations from a single image using a fine-tuned pretrained video diffusion model, outperforming existing methods in efficiency and generalizability.
Junjie Wu, Jiangnan Li, Yuqing Li +6 authors
A new training paradigm and situated embedding models (SitEmb) enhance retrieval performance by conditioning short text chunks on broader context windows, outperforming state-of-the-art models with fewer parameters.
Pratyush Maini, Vineeth Dorna, Parth Doshi +26 authors
BeyondWeb, a synthetic data generation framework, outperforms existing datasets and accelerates training for large language models by optimizing multiple factors.
Chin-Yang Lin, Cheng Sun, Fu-En Yang +3 authors
LongSplat improves novel view synthesis from long videos with irregular motion through joint optimization, robust pose estimation, and efficient anchor formation.
Lin Long, Yichen He, Wentao Ye +5 authors
M3-Agent, a multimodal agent with long-term memory, performs multi-turn reasoning and outperforms baselines on a new long-video question answering benchmark.
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