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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.
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.
Neta Glazer, Yael Segal-Feldman, Hilit Segev +6 authors
Interpretability methods like logit lens, linear probing, and activation patching are applied to ASR to uncover internal dynamics, repetition hallucinations, and semantic biases, enhancing model transparency and robustness.
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.
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.
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.
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.
Xinrun Xu, Pi Bu, Ye Wang +7 authors
DeepPHY evaluates Vision Language Models' physical reasoning and control through simulated environments with varying difficulty levels.
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.
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.
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.
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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