Explore · 每周精选
发现最受关注的研究论文,追踪研究趋势,订阅感兴趣的期刊与关键词。
606 篇论文 · 按点赞排序
Kaichen Zhang, Keming Wu, Zuhao Yang +5 authors
OpenMMReasoner, a two-stage training approach combining supervised fine-tuning and reinforcement learning, enhances multimodal reasoning performance through rigorous data curation and improved training strategies.
Tianqing Fang, Zhisong Zhang, Xiaoyang Wang +10 authors
Cognitive Kernel-Pro is an open-source multi-module agent framework that enhances AI agent robustness and performance through data curation and novel test-time strategies, achieving state-of-the-art results.
Jianhong Bai, Xiaoshi Wu, Xintao Wang +9 authors
SemanticGen addresses slow convergence and computational costs in video generation by using a two-stage diffusion model approach that first generates semantic features and then VAE latents, leading to faster convergence and high-quality results.
Daniil Selikhanovych, David Li, Aleksei Leonov +6 authors
RSD is a distillation method for ResShift, a top diffusion-based super-resolution model, that achieves high-quality results with fewer parameters and GPU memory compared to other methods.
Samuel Schmidgall, Yusheng Su, Ze Wang +6 authors
Agent Laboratory, an LLM-based framework, accelerates scientific research by automating the entire process from idea to report, resulting in high-quality outputs with reduced expenses.
Rui-Jie Zhu, Tianhao Peng, Tianhao Cheng +30 authors
Latent reasoning in Large Language Models (LLMs) performs multi-step inference in continuous hidden states, enhancing reasoning capabilities without token-level supervision, and includes methodologies like activation-based recurrence and infinite-depth reasoning via masked diffusion models.
Haoran Wei, Yaofeng Sun, Yukun Li
DeepSeek-OCR uses optical 2D mapping to compress long contexts, achieving high OCR precision with reduced vision tokens and demonstrating practical value in document processing.
Ding Chen, Simin Niu, Kehang Li +6 authors
HaluMem, a benchmark for evaluating memory hallucinations in AI systems, identifies and analyzes hallucinations across memory extraction, updating, and question answering stages using large-scale human-AI interaction datasets.
Eliahu Horwitz, Nitzan Kurer, Jonathan Kahana +2 authors
An atlas of Hugging Face's model repository provides visualizations and analysis, with methods for mapping undocumented areas based on structural priors.
Yibin Wang, Zhimin Li, Yuhang Zang +4 authors
A unified multimodal reward model that incorporates long chains of thought reasoning improves reliability and accuracy in vision reward tasks through exploration-driven reinforcement learning.
Juanxi Tian, Siyuan Li, Conghui He +2 authors
A benchmark for chained text-to-multi-image generation assesses models' ability to model dynamic causal processes and world knowledge, revealing that unified multimodal models outperform specialized ones but still struggle with spatiotemporal consistency.
Nikai Du, Zhennan Chen, Zhizhou Chen +5 authors
TextCrafter is a progressive method that enhances the generation of intricate visual text within images, addressing issues like distortion, blurriness, and omissions through token focus enhancement.
Xueqing Peng, Lingfei Qian, Yan Wang +41 authors
MultiFinBen is a multilingual and multimodal benchmark for financial domain tasks, evaluating LLMs across modalities and linguistic settings, revealing challenges in complex cross-lingual and multimodal financial reasoning.
Zheyuan Yang, Lyuhao Chen, Arman Cohan +1 authors
Two post-training strategies, distillation and RLVR, enable inference-time scaling in table reasoning tasks, resulting in a model (Table-R1-Zero) that matches GPT-4.1's performance using fewer parameters and shows strong generalization.
Hanrong Ye, Chao-Han Huck Yang, Arushi Goel +29 authors
OmniVinci, an open-source omni-modal LLM, enhances cross-modal understanding and performance across audio, vision, and robotics applications with innovative architecture and efficient data curation.
Jia-Nan Li, Jian Guan, Wei Wu +1 authors
ReFusion, a novel masked diffusion model, improves performance and efficiency by using slot-based parallel decoding, achieving superior results compared to autoregressive models and traditional masked diffusion models.
Kuan Li, Zhongwang Zhang, Huifeng Yin +14 authors
WebSailor, a post-training methodology, enhances open-source models with systematic uncertainty reduction, matching proprietary agents' performance in complex information-seeking tasks.
Yichao Fu, Xuewei Wang, Yuandong Tian +1 authors
DeepConf enhances reasoning efficiency and performance by filtering low-quality reasoning traces using model-internal confidence signals, achieving high accuracy and reducing token generation.
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.
Zichen Liu, Anya Sims, Keyu Duan +16 authors
GEM, an open-source environment simulator, facilitates experience-based learning for large language models by providing a standardized framework and diverse environments for training and benchmarking reinforcement learning algorithms.
Shiyu Liu, Yucheng Han, Peng Xing +21 authors
Step1X-Edit, an image editing model that uses multimodal LLM and diffusion image decoder, outperforms open-source models and approaches proprietary models in quality.
Yuxiang Ji, Ziyu Ma, Yong Wang +3 authors
Tree-based Group Relative Policy Optimization (Tree-GRPO) enhances reinforcement learning for large language models by using tree search to improve rollouts and estimate grouped relative advantages, outperforming chain-based methods.
Jiayi Zhang, Yiran Peng, Fanqi Kong +12 authors
AutoEnv and AutoEnv-36 provide a standardized framework and dataset for evaluating cross-environment learning in agents, highlighting the challenges and limitations of existing learning methods.
Sergey Pletenev, Maria Marina, Daniil Moskovskiy +4 authors
Low-rank adaptation (LoRA) effectively updates LLMs with new knowledge but risks degrading performance on external benchmarks due to data bias and overconfidence.
Xiaofeng Mao, Shaoheng Lin, Zhen Li +7 authors
A framework for generating and exploring interactive, high-fidelity video worlds from images using a Masked Video Diffusion Transformer, advanced sampling techniques, and model acceleration.
Abdelrahman Abouelenin, Atabak Ashfaq, Adam Atkinson +70 authors
Phi-4-Mini and Phi-4-Multimodal are compact yet highly capable language and multimodal models, featuring advanced attention mechanisms and LoRA adapters for efficient and powerful reasoning across various tasks.
Yifan Zhang, Yifeng Liu, Huizhuo Yuan +4 authors
T6, a new Transformer architecture using Tensor Product Attention, improves language model performance and memory efficiency, allowing for longer sequence processing.
Boqiang Zhang, Kehan Li, Zesen Cheng +12 authors
A vision-centric multimodal foundation model, VideoLLaMA3, improves image and video understanding through strategic training stages and adaptive vision token encoding.
Yibin Wang, Zhimin Li, Yuhang Zang +6 authors
Pref-GRPO, a pairwise preference reward-based GRPO method, enhances text-to-image generation by mitigating reward hacking and improving stability, while UniGenBench provides a comprehensive benchmark for evaluating T2I models.
Vladislav Pedashenko, Laida Kushnareva, Yana Khassan Nibal +5 authors
The study explores intrinsic dimension in large language models through cross-encoder analysis, linguistic features, and sparse autoencoders, revealing its independence from entropy, genre-specific stratification, and causal features related to text type.
北京市昌平区探索星信息技术及软件开发工作室
京ICP备2026059466号