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Junjie Wang

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Daily Paper CastDaily Paper CastAnyCap Project: A Unified Framework, Dataset, and Benchmark for Controllable Omni-modal Captioning 🤗 Upvotes: 30 | cs.CV Authors: Yiming Ren, Zhiqiang Lin, Yu Li, Gao Meng, Weiyun Wang, Junjie Wang, Zicheng Lin, Jifeng Dai, Yujiu Yang, Wenhai Wang, Ruihang Chu Title: AnyCap Project: A Unified Framework, Dataset, and Benchmark for Controllable Omni-modal Captioning Arxiv: http://arxiv.org/abs/2507.12841v1 Abstract: Controllable captioning is essential for precise multimodal alignment and instruction following, yet existing models often lack fine-grained control and reliable evaluation protocols. To address this gap, we present the AnyCap Project, an integrated solution spanning model, dataset, and evaluation. We introduce Any...2025-07-1922 min101 Weekly101 Weekly时尚女魔头Anna Wintour卸任：数字时代崩塌的时尚权威与“帝王式主编”神话破灭 | 20250707统治全球时尚界长达37年的“女魔头”Anna Wintour，突然卸任美版《Vogue》总编辑，震动整个行业。这不仅是一次人事变动，更像是一个旧时代落幕：过去的时尚界是一个高度封闭、等级分明的审美系统，如今随着互联网与社交媒体的全面成熟，由少数“帝王式主编”构筑的时尚帝国已然权威崩塌。在短视频席卷一切的今天，谁还有资格定义“时尚”？传统纸媒们又该如何自救？ 【主播】 Yiwen，硅谷101研究员 【嘉宾】 Junjie Wang，前Vogue Business编辑、Vogue Hong Kong专题编辑 【101Weekly简介】 「101Weekly」是硅谷101出品的一档轻解读节目，每周由我们的三位主播复盘三个商业热点事件，每期10分钟左右，并请来行业专家来一手深度分析。每周30分钟，轻松了解一周新闻大事件。 【关注我们】 音频版：小宇宙｜苹果播客｜Spotify 视频版：BiliBIli｜Youtube｜视频号｜抖音2025-07-0808 minDaily Paper CastDaily Paper CastGLM-4.1V-Thinking: Towards Versatile Multimodal Reasoning with Scalable Reinforcement Learning 🤗 Upvotes: 141 | cs.CV, cs.AI, cs.LG Authors: GLM-V Team, :, Wenyi Hong, Wenmeng Yu, Xiaotao Gu, Guo Wang, Guobing Gan, Haomiao Tang, Jiale Cheng, Ji Qi, Junhui Ji, Lihang Pan, Shuaiqi Duan, Weihan Wang, Yan Wang, Yean Cheng, Zehai He, Zhe Su, Zhen Yang, Ziyang Pan, Aohan Zeng, Baoxu Wang, Boyan Shi, Changyu Pang, Chenhui Zhang, Da Yin, Fan Yang, Guoqing Chen, Jiazheng Xu, Jiali Chen, Jing Chen, Jinhao Chen, Jinghao Lin, Jinjiang Wang, Junjie Chen, Leqi Lei, Letian Gong, Leyi Pan, Mingzhi Zhang, Qinkai Zheng, Sheng Yang, Shi Zhong, Shiyu Huang, Shuyuan Zhao, Siyan Xue, Sha...2025-07-0324 minDaily Paper CastDaily Paper CastOThink-R1: Intrinsic Fast/Slow Thinking Mode Switching for Over-Reasoning Mitigation 🤗 Upvotes: 28 | cs.AI Authors: Shengjia Zhang, Junjie Wu, Jiawei Chen, Changwang Zhang, Xingyu Lou, Wangchunshu Zhou, Sheng Zhou, Can Wang, Jun Wang Title: OThink-R1: Intrinsic Fast/Slow Thinking Mode Switching for Over-Reasoning Mitigation Arxiv: http://arxiv.org/abs/2506.02397v1 Abstract: Recent advanced large reasoning models (LRMs) leverage extended chain-of-thought (CoT) reasoning to solve complex tasks, achieving state-of-the-art performance. Despite their success, we identify a critical issue: a substantial portion of simple tasks solved by LRMs can also be addressed by non-reasoning LLMs using significantly fewer tokens, indicating the...2025-06-0524 minDaily Paper CastDaily Paper CastSynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond 🤗 Upvotes: 43 | cs.AI, cs.CL Authors: Junteng Liu, Yuanxiang Fan, Zhuo Jiang, Han Ding, Yongyi Hu, Chi Zhang, Yiqi Shi, Shitong Weng, Aili Chen, Shiqi Chen, Yunan Huang, Mozhi Zhang, Pengyu Zhao, Junjie Yan, Junxian He Title: SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond Arxiv: http://arxiv.org/abs/2505.19641v3 Abstract: Recent advances such as OpenAI-o1 and DeepSeek R1 have demonstrated the potential of Reinforcement Learning (RL) to enhance reasoning abilities in Large Language Models (LLMs). While open-source replication efforts have pri...2025-05-2921 minDaily Paper CastDaily Paper CastShifting AI Efficiency From Model-Centric to Data-Centric Compression 🤗 Upvotes: 124 | cs.CL, cs.AI, cs.CV Authors: Xuyang Liu, Zichen Wen, Shaobo Wang, Junjie Chen, Zhishan Tao, Yubo Wang, Xiangqi Jin, Chang Zou, Yiyu Wang, Chenfei Liao, Xu Zheng, Honggang Chen, Weijia Li, Xuming Hu, Conghui He, Linfeng Zhang Title: Shifting AI Efficiency From Model-Centric to Data-Centric Compression Arxiv: http://arxiv.org/abs/2505.19147v1 Abstract: The rapid advancement of large language models (LLMs) and multi-modal LLMs (MLLMs) has historically relied on model-centric scaling through increasing parameter counts from millions to hundreds of billions to drive performance gai...2025-05-2822 minDaily Paper CastDaily Paper CastOne RL to See Them All: Visual Triple Unified Reinforcement Learning 🤗 Upvotes: 51 | cs.CV, cs.CL Authors: Yan Ma, Linge Du, Xuyang Shen, Shaoxiang Chen, Pengfei Li, Qibing Ren, Lizhuang Ma, Yuchao Dai, Pengfei Liu, Junjie Yan Title: One RL to See Them All: Visual Triple Unified Reinforcement Learning Arxiv: http://arxiv.org/abs/2505.18129v1 Abstract: Reinforcement learning (RL) has significantly advanced the reasoning capabilities of vision-language models (VLMs). However, the use of RL beyond reasoning tasks remains largely unexplored, especially for perceptionintensive tasks like object detection and grounding. We propose V-Triune, a Visual Triple Unified Reinforcement Learning sys...2025-05-2720 minDaily Paper CastDaily Paper CastDeCLIP: Decoupled Learning for Open-Vocabulary Dense Perception 🤗 Upvotes: 36 | cs.CV Authors: Junjie Wang, Bin Chen, Yulin Li, Bin Kang, Yichi Chen, Zhuotao Tian Title: DeCLIP: Decoupled Learning for Open-Vocabulary Dense Perception Arxiv: http://arxiv.org/abs/2505.04410v1 Abstract: Dense visual prediction tasks have been constrained by their reliance on predefined categories, limiting their applicability in real-world scenarios where visual concepts are unbounded. While Vision-Language Models (VLMs) like CLIP have shown promise in open-vocabulary tasks, their direct application to dense prediction often leads to suboptimal performance due to limitations in local feature representation. In this wor...2025-05-1619 minDaily Paper CastDaily Paper CastMiniMax-Speech: Intrinsic Zero-Shot Text-to-Speech with a Learnable Speaker Encoder 🤗 Upvotes: 83 | eess.AS, cs.SD Authors: Bowen Zhang, Congchao Guo, Geng Yang, Hang Yu, Haozhe Zhang, Heidi Lei, Jialong Mai, Junjie Yan, Kaiyue Yang, Mingqi Yang, Peikai Huang, Ruiyang Jin, Sitan Jiang, Weihua Cheng, Yawei Li, Yichen Xiao, Yiying Zhou, Yongmao Zhang, Yuan Lu, Yucen He Title: MiniMax-Speech: Intrinsic Zero-Shot Text-to-Speech with a Learnable Speaker Encoder Arxiv: http://arxiv.org/abs/2505.07916v1 Abstract: We introduce MiniMax-Speech, an autoregressive Transformer-based Text-to-Speech (TTS) model that generates high-quality speech. A key innovation is our learnable speaker encoder, which extracts timbre fea...2025-05-1521 minDaily Paper CastDaily Paper CastSeed1.5-VL Technical Report 🤗 Upvotes: 86 | cs.CV, cs.AI Authors: Dong Guo, Faming Wu, Feida Zhu, Fuxing Leng, Guang Shi, Haobin Chen, Haoqi Fan, Jian Wang, Jianyu Jiang, Jiawei Wang, Jingji Chen, Jingjia Huang, Kang Lei, Liping Yuan, Lishu Luo, Pengfei Liu, Qinghao Ye, Rui Qian, Shen Yan, Shixiong Zhao, Shuai Peng, Shuangye Li, Sihang Yuan, Sijin Wu, Tianheng Cheng, Weiwei Liu, Wenqian Wang, Xianhan Zeng, Xiao Liu, Xiaobo Qin, Xiaohan Ding, Xiaojun Xiao, Xiaoying Zhang, Xuanwei Zhang, Xuehan Xiong, Yanghua Peng, Yangrui Chen, Yanwei Li, Yanxu Hu, Yi Lin, Yiyuan Hu, Yiyuan Zhang, Youbin Wu, Yu Li, Yudong Liu, Yue...2025-05-1420 minDaily Paper CastDaily Paper CastKimi-VL Technical Report 🤗 Upvotes: 71 | cs.CV Authors: Kimi Team, Angang Du, Bohong Yin, Bowei Xing, Bowen Qu, Bowen Wang, Cheng Chen, Chenlin Zhang, Chenzhuang Du, Chu Wei, Congcong Wang, Dehao Zhang, Dikang Du, Dongliang Wang, Enming Yuan, Enzhe Lu, Fang Li, Flood Sung, Guangda Wei, Guokun Lai, Han Zhu, Hao Ding, Hao Hu, Hao Yang, Hao Zhang, Haoning Wu, Haotian Yao, Haoyu Lu, Heng Wang, Hongcheng Gao, Huabin Zheng, Jiaming Li, Jianlin Su, Jianzhou Wang, Jiaqi Deng, Jiezhong Qiu, Jin Xie, Jinhong Wang, Jingyuan Liu, Junjie Yan, Kun Ouyang, Liang Chen, Lin Sui, Longhui Yu, Mengfan Dong, Mengnan Dong, Nuo...2025-04-1223 minKenneth TactKenneth TactDr. Junjie Wang Tsinghua University, China2025-04-0933 minDaily Paper CastDaily Paper CastThe Stochastic Parrot on LLM's Shoulder: A Summative Assessment of Physical Concept Understanding 🤗 Upvotes: 35 | cs.CL, cs.AI, cs.CV, cs.LG Authors: Mo Yu, Lemao Liu, Junjie Wu, Tsz Ting Chung, Shunchi Zhang, Jiangnan Li, Dit-Yan Yeung, Jie Zhou Title: The Stochastic Parrot on LLM's Shoulder: A Summative Assessment of Physical Concept Understanding Arxiv: http://arxiv.org/abs/2502.08946v1 Abstract: In a systematic way, we investigate a widely asked question: Do LLMs really understand what they say?, which relates to the more familiar term Stochastic Parrot. To this end, we propose a summative assessment over a carefully designed physical con...2025-02-1521 minDaily Paper CastDaily Paper CastDeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning 🤗 Upvotes: 109 | cs.CL, cs.AI, cs.LG Authors: DeepSeek-AI, Daya Guo, Dejian Yang, Haowei Zhang, Junxiao Song, Ruoyu Zhang, Runxin Xu, Qihao Zhu, Shirong Ma, Peiyi Wang, Xiao Bi, Xiaokang Zhang, Xingkai Yu, Yu Wu, Z. F. Wu, Zhibin Gou, Zhihong Shao, Zhuoshu Li, Ziyi Gao, Aixin Liu, Bing Xue, Bingxuan Wang, Bochao Wu, Bei Feng, Chengda Lu, Chenggang Zhao, Chengqi Deng, Chenyu Zhang, Chong Ruan, Damai Dai, Deli Chen, Dongjie Ji, Erhang Li, Fangyun Lin, Fucong Dai, Fuli Luo, Guangbo Hao, Guanting Chen, Guowei Li, H. Zhang, Han Bao, Hanwei Xu, Haocheng Wang, Honghui Ding, Hua...2025-01-2421 minDaily Paper CastDaily Paper CastKimi k1.5: Scaling Reinforcement Learning with LLMs 🤗 Upvotes: 39 | cs.AI, cs.LG Authors: Kimi Team, Angang Du, Bofei Gao, Bowei Xing, Changjiu Jiang, Cheng Chen, Cheng Li, Chenjun Xiao, Chenzhuang Du, Chonghua Liao, Chuning Tang, Congcong Wang, Dehao Zhang, Enming Yuan, Enzhe Lu, Fengxiang Tang, Flood Sung, Guangda Wei, Guokun Lai, Haiqing Guo, Han Zhu, Hao Ding, Hao Hu, Hao Yang, Hao Zhang, Haotian Yao, Haotian Zhao, Haoyu Lu, Haoze Li, Haozhen Yu, Hongcheng Gao, Huabin Zheng, Huan Yuan, Jia Chen, Jianhang Guo, Jianlin Su, Jianzhou Wang, Jie Zhao, Jin Zhang, Jingyuan Liu, Junjie Yan, Junyan Wu, Lidong Shi, Ling Ye, Longhui Yu, Men...2025-01-2418 minDaily Paper CastDaily Paper CastAgent-R: Training Language Model Agents to Reflect via Iterative Self-Training 🤗 Upvotes: 61 | cs.AI Authors: Siyu Yuan, Zehui Chen, Zhiheng Xi, Junjie Ye, Zhengyin Du, Jiecao Chen Title: Agent-R: Training Language Model Agents to Reflect via Iterative Self-Training Arxiv: http://arxiv.org/abs/2501.11425v1 Abstract: Large Language Models (LLMs) agents are increasingly pivotal for addressing complex tasks in interactive environments. Existing work mainly focuses on enhancing performance through behavior cloning from stronger experts, yet such approaches often falter in real-world applications, mainly due to the inability to recover from errors. However, step-level critique data is difficult and expensive to...2025-01-2320 minDaily Paper CastDaily Paper CastUI-TARS: Pioneering Automated GUI Interaction with Native Agents 🤗 Upvotes: 31 | cs.AI, cs.CL, cs.CV, cs.HC Authors: Yujia Qin, Yining Ye, Junjie Fang, Haoming Wang, Shihao Liang, Shizuo Tian, Junda Zhang, Jiahao Li, Yunxin Li, Shijue Huang, Wanjun Zhong, Kuanye Li, Jiale Yang, Yu Miao, Woyu Lin, Longxiang Liu, Xu Jiang, Qianli Ma, Jingyu Li, Xiaojun Xiao, Kai Cai, Chuang Li, Yaowei Zheng, Chaolin Jin, Chen Li, Xiao Zhou, Minchao Wang, Haoli Chen, Zhaojian Li, Haihua Yang, Haifeng Liu, Feng Lin, Tao Peng, Xin Liu, Guang Shi Title: UI-TARS: Pioneering Automated GUI Interaction with Native Agents Arxiv: htt...2025-01-2320 minDaily Paper CastDaily Paper CastMegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval 🤗 Upvotes: 44 | cs.CV, cs.CL Authors: Junjie Zhou, Zheng Liu, Ze Liu, Shitao Xiao, Yueze Wang, Bo Zhao, Chen Jason Zhang, Defu Lian, Yongping Xiong Title: MegaPairs: Massive Data Synthesis For Universal Multimodal Retrieval Arxiv: http://arxiv.org/abs/2412.14475v1 Abstract: Despite the rapidly growing demand for multimodal retrieval, progress in this field remains severely constrained by a lack of training data. In this paper, we introduce MegaPairs, a novel data synthesis method that leverages vision language models (VLMs) and open-domain images, together with a massive synthetic dat...2024-12-2123 minPapers Read on AIPapers Read on AIML-Bench: Evaluating Large Language Models and Agents for Machine Learning Tasks on Repository-Level CodeDespite Large Language Models (LLMs) like GPT-4 achieving impressive results in function-level code generation, they struggle with repository-scale code understanding (e.g., coming up with the right arguments for calling routines), requiring a deeper comprehension of complex file interactions. Also, recently, people have developed LLM agents that attempt to interact with repository code (e.g., compiling and evaluating its execution), prompting the need to evaluate their performance. These gaps have motivated our development of ML-Bench, a benchmark rooted in real-world programming applications that leverage existing code repositories to perform tasks. Addressing the need for LLMs to interpret long code contexts...2024-07-0827 minOperative Neurosurgery Speaks!​Operative Neurosurgery Speaks!​ChineseJunjie Wang, MD, Department of Neurosurgery, Beijing Hospital, National Center of Gerontology, Beijing, China Transcript: http://links.lww.com/ONS/B1082024-04-2303 minWrestling With EntertainmentWrestling With EntertainmentWrestling With; Big Sam Interview #wrestlingwith #Interviews Big Sam  @sjdburgess  in our biggest interview yet! We talk winning the MKW and KOPW Championships, The Stable, Tug of War champion? Having a painted portrait, a bizzare adventure in China, and much more! Follow We Sam on socialsLinktree https://linktr.ee/sjdburgessInstagram https://www.instagram.com/sjdburgess/?hl=enX https://twitter.com/sjdburgess/Facebook https://www.facebook.com/SJDBurgessYouTube https://www.youtube.com/@sjdburgessCrystal, Syuou Fujiwara & Big Sam & Un...2024-03-071h 55Wrestling With EntertainmentWrestling With EntertainmentUncle Money Interview #wrestlingwith #Interviews Uncle Money. We talk, match against Yoshi Tatsu, Ho Ho Lun, and Zombie Dragon, rivalry against Zombie Dragon, relationship with the Stable, wrestling in South Korea, acting, mobile game ads, raping, anime and much more! Follow We Uncle on socialsX https://twitter.com/payunclemoney?lang=enInstagram https://www.instagram.com/_unclemoney/?hl=enFacebook https://www.facebook.com/payunclemoney/?locale=it_ITBlack Beyond Borders YouTube https://www.youtube.com/@blackbeyondborders2024FUNCTIONZ PODCASTS https://www.youtube.com/@FUNCTIONZPODCASTS...2024-02-291h 283DPOD: Insight from 3D Printing Pros3DPOD: Insight from 3D Printing ProsResearchers 3D Print Miniscule On-Chip Microbatteries with Incredible PotentialWe are living in an incredibly shrinking world -- a world in which we see electronics decrease in size at an almost unbelievable rate. Think about the size of computer memory, music players, and cell phones. Each and every year, the size of microchips get smaller, while their capacities and abilities continue to increase. One area which researchers have been trying to innovate upon, with not all that much success, is in the production of batteries. Battery sizes have not been keeping up with the decreasing size of other electronics, thus creating some perplexing issues for electronic manufacturers and engineers. Th...2015-05-1600 min