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PODCAST

Daily Paper Cast

Jingwen Liang, Gengyu Wang

We update every weekday to discuss highest-voted papers from Huggingface Daily Paper (https://huggingface.co/papers). Both the podcast scripts and audio are generated by AI. Feedback and suggestions are welcome! Email us: dailypapercast.ai@gmail.com Creator: Jingwen Liang, 3D ML, https://www.linkedin.com/in/jingwen-liang/ Gengyu Wang, LLM ML, http://wanggengyu.com Listen on: Spotify: https://open.spotify.com/show/21nrhmdaA8qoBiH8q03NXL Apple Podcast:

science

All Episodes

18:21

Agentic Reward Modeling: Integrating Human...

Daily Paper Cast ·

2025/02/28

🤗 Upvotes: 15 | cs.CL, cs.AI Authors: Hao Peng, Yunjia Qi, Xiaozhi Wang, Zijun Yao, Bin Xu, Lei Hou, Juanzi Li Title: Agentic Reward Modeling: Integrating Human Preferences with Verifiable Correctness Signals for Reliable Reward Systems Arxiv: http://arxiv.org/abs/2502.19328v1 Abstract: Reward models (RMs) are crucial for the training and inference-time scaling up of large

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22:49

Can Language Models Falsify? Evaluating Algorithmic...

Daily Paper Cast ·

2025/02/28

🤗 Upvotes: 13 | cs.LG, cs.SE Authors: Shiven Sinha, Shashwat Goel, Ponnurangam Kumaraguru, Jonas Geiping, Matthias Bethge, Ameya Prabhu Title: Can Language Models Falsify? Evaluating Algorithmic Reasoning with Counterexample Creation Arxiv: http://arxiv.org/abs/2502.19414v1 Abstract: There is growing excitement about the potential of Language Models (LMs) to accelerate

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19:51

Rank1: Test-Time Compute for Reranking in Information...

Daily Paper Cast ·

2025/02/28

🤗 Upvotes: 11 | cs.IR, cs.CL, cs.LG Authors: Orion Weller, Kathryn Ricci, Eugene Yang, Andrew Yates, Dawn Lawrie, Benjamin Van Durme Title: Rank1: Test-Time Compute for Reranking in Information Retrieval Arxiv: http://arxiv.org/abs/2502.18418v1 Abstract: We introduce Rank1, the first reranking model trained to take advantage of test-time compute. Rank1 demonstrates the

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26:26

MLGym: A New Framework and Benchmark for Advancing AI...

Daily Paper Cast ·

2025/02/22

🤗 Upvotes: 122 | cs.CL, cs.AI, cs.LGAuthors: Deepak Nathani, Lovish Madaan, Nicholas Roberts, Nikolay Bashlykov, Ajay Menon, Vincent Moens, Amar Budhiraja, Despoina Magka, Vladislav Vorotilov, Gaurav Chaurasia, Dieuwke Hupkes, Ricardo Silveira Cabral, Tatiana Shavrina, Jakob Foerster, Yoram Bachrach, William Yang Wang, Roberta Raileanu Title: MLGym: A New Framework and Benchmark for Advancing AI Research Agents

en

25:23

SigLIP 2: Multilingual Vision-Language Encoders with...

Daily Paper Cast ·

2025/02/22

🤗 Upvotes: 82 | cs.CV, cs.AI Authors: Michael Tschannen, Alexey Gritsenko, Xiao Wang, Muhammad Ferjad Naeem, Ibrahim Alabdulmohsin, Nikhil Parthasarathy, Talfan Evans, Lucas Beyer, Ye Xia, Basil Mustafa, Olivier Hénaff, Jeremiah Harmsen, Andreas Steiner, Xiaohua Zhai Title: SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features Arxiv:

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24:06

SuperGPQA: Scaling LLM Evaluation across 285 Graduate...

Daily Paper Cast ·

2025/02/22

🤗 Upvotes: 81 | cs.CL Authors: M-A-P Team, Xinrun Du, Yifan Yao, Kaijing Ma, Bingli Wang, Tianyu Zheng, Kang Zhu, Minghao Liu, Yiming Liang, Xiaolong Jin, Zhenlin Wei, Chujie Zheng, Kaixing Deng, Shuyue Guo, Shian Jia, Sichao Jiang, Yiyan Liao, Rui Li, Qinrui Li, Sirun Li, Yizhi Li, Yunwen Li, Dehua Ma, Yuansheng Ni, Haoran Que, Qiyao Wang, Zhoufutu Wen, Siwei Wu, Tianshun Xing, Ming Xu, Zhenzhu Yang, Zekun Moore Wang, Junting Zhou, Yuelin Bai,

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22:43

How Much Knowledge Can You Pack into a LoRA Adapter...

Daily Paper Cast ·

2025/02/22

🤗 Upvotes: 51 | cs.CL Authors: Sergey Pletenev, Maria Marina, Daniil Moskovskiy, Vasily Konovalov, Pavel Braslavski, Alexander Panchenko, Mikhail Salnikov Title: How Much Knowledge Can You Pack into a LoRA Adapter without Harming LLM? Arxiv: http://arxiv.org/abs/2502.14502v1 Abstract: The performance of Large Language Models (LLMs) on many tasks is greatly limited by the

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24:06

S*: Test Time Scaling for Code Generation

Daily Paper Cast ·

2025/02/22

🤗 Upvotes: 39 | cs.LG, cs.AI Authors: Dacheng Li, Shiyi Cao, Chengkun Cao, Xiuyu Li, Shangyin Tan, Kurt Keutzer, Jiarong Xing, Joseph E. Gonzalez, Ion Stoica Title: S*: Test Time Scaling for Code Generation Arxiv: http://arxiv.org/abs/2502.14382v1 Abstract: Increasing test-time compute for LLMs shows promise across domains but remains underexplored in code generation, despite

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24:51

Logic-RL: Unleashing LLM Reasoning with Rule-Based...

Daily Paper Cast ·

2025/02/22

🤗 Upvotes: 24 | cs.CL, cs.AI Authors: Tian Xie, Zitian Gao, Qingnan Ren, Haoming Luo, Yuqian Hong, Bryan Dai, Joey Zhou, Kai Qiu, Zhirong Wu, Chong Luo Title: Logic-RL: Unleashing LLM Reasoning with Rule-Based Reinforcement Learning Arxiv: http://arxiv.org/abs/2502.14768v1 Abstract: Inspired by the success of DeepSeek-R1, we explore the potential of rule-based reinforcement

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21:29

Discovering highly efficient low-weight quantum...

Daily Paper Cast ·

2025/02/22

🤗 Upvotes: 22 | quant-ph, cs.AI, cs.IT, cs.LG, math.IT Authors: Austin Yubo He, Zi-Wen Liu Title: Discovering highly efficient low-weight quantum error-correcting codes with reinforcement learning Arxiv: http://arxiv.org/abs/2502.14372v1 Abstract: The realization of scalable fault-tolerant quantum computing is expected to hinge on quantum error-correcting codes. In the quest for

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19:43

LongWriter-V: Enabling Ultra-Long and High-Fidelity...

Daily Paper Cast ·

2025/02/22

🤗 Upvotes: 20 | cs.CV, cs.AI, cs.CL Authors: Shangqing Tu, Yucheng Wang, Daniel Zhang-Li, Yushi Bai, Jifan Yu, Yuhao Wu, Lei Hou, Huiqin Liu, Zhiyuan Liu, Bin Xu, Juanzi Li Title: LongWriter-V: Enabling Ultra-Long and High-Fidelity Generation in Vision-Language Models Arxiv: http://arxiv.org/abs/2502.14834v1 Abstract: Existing Large Vision-Language Models (LVLMs) can process

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23:15

Does Time Have Its Place? Temporal Heads: Where...

Daily Paper Cast ·

2025/02/22

🤗 Upvotes: 18 | cs.CL, cs.AI Authors: Yein Park, Chanwoong Yoon, Jungwoo Park, Minbyul Jeong, Jaewoo Kang Title: Does Time Have Its Place? Temporal Heads: Where Language Models Recall Time-specific Information Arxiv: http://arxiv.org/abs/2502.14258v1 Abstract: While the ability of language models to elicit facts has been widely investigated, how they handle temporally changing

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23:24

S$^2$R: Teaching LLMs to Self-verify and Self-correct...

Daily Paper Cast ·

2025/02/22

🤗 Upvotes: 15 | cs.CL, cs.LG Authors: Ruotian Ma, Peisong Wang, Cheng Liu, Xingyan Liu, Jiaqi Chen, Bang Zhang, Xin Zhou, Nan Du, Jia Li Title: S$^2$R: Teaching LLMs to Self-verify and Self-correct via Reinforcement Learning Arxiv: http://arxiv.org/abs/2502.12853v1 Abstract: Recent studies have demonstrated the effectiveness of LLM test-time scaling. However, existing approaches

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21:11

Qwen2.5-VL Technical Report

Daily Paper Cast ·

2025/02/21

🤗 Upvotes: 97 | cs.CV, cs.CLAuthors: Shuai Bai, Keqin Chen, Xuejing Liu, Jialin Wang, Wenbin Ge, Sibo Song, Kai Dang, Peng Wang, Shijie Wang, Jun Tang, Humen Zhong, Yuanzhi Zhu, Mingkun Yang, Zhaohai Li, Jianqiang Wan, Pengfei Wang, Wei Ding, Zheren Fu, Yiheng Xu, Jiabo Ye, Xi Zhang, Tianbao Xie, Zesen Cheng, Hang Zhang, Zhibo Yang, Haiyang Xu, Junyang Lin Title: Qwen2.5-VL Technical Report Arxiv:

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20:45

RAD: Training an End-to-End Driving Policy via...

Daily Paper Cast ·

2025/02/21

🤗 Upvotes: 31 | cs.CV, cs.RO Authors: Hao Gao, Shaoyu Chen, Bo Jiang, Bencheng Liao, Yiang Shi, Xiaoyang Guo, Yuechuan Pu, Haoran Yin, Xiangyu Li, Xinbang Zhang, Ying Zhang, Wenyu Liu, Qian Zhang, Xinggang Wang Title: RAD: Training an End-to-End Driving Policy via Large-Scale 3DGS-based Reinforcement Learning Arxiv: http://arxiv.org/abs/2502.13144v1 Abstract: Existing end-to-end

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24:25

SongGen: A Single Stage Auto-regressive Transformer...

Daily Paper Cast ·

2025/02/21

🤗 Upvotes: 28 | cs.SD, cs.AI Authors: Zihan Liu, Shuangrui Ding, Zhixiong Zhang, Xiaoyi Dong, Pan Zhang, Yuhang Zang, Yuhang Cao, Dahua Lin, Jiaqi Wang Title: SongGen: A Single Stage Auto-regressive Transformer for Text-to-Song Generation Arxiv: http://arxiv.org/abs/2502.13128v1 Abstract: Text-to-song generation, the task of creating vocals and accompaniment from textual inputs,

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20:12

MoM: Linear Sequence Modeling with Mixture-of-Memories

Daily Paper Cast ·

2025/02/21

🤗 Upvotes: 22 | cs.CL, cs.AI, cs.LG Authors: Jusen Du, Weigao Sun, Disen Lan, Jiaxi Hu, Yu Cheng Title: MoM: Linear Sequence Modeling with Mixture-of-Memories Arxiv: http://arxiv.org/abs/2502.13685v1 Abstract: Linear sequence modeling methods, such as linear attention, state space modeling, and linear RNNs, offer significant efficiency improvements by reducing the complexity of

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21:25

Is That Your Final Answer? Test-Time Scaling Improves...

Daily Paper Cast ·

2025/02/21

🤗 Upvotes: 22 | cs.CL Authors: William Jurayj, Jeffrey Cheng, Benjamin Van Durme Title: Is That Your Final Answer? Test-Time Scaling Improves Selective Question Answering Arxiv: http://arxiv.org/abs/2502.13962v1 Abstract: Scaling the test-time compute of large language models has demonstrated impressive performance on reasoning benchmarks. However, existing evaluations of

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22:44

Craw4LLM: Efficient Web Crawling for LLM Pretraining

Daily Paper Cast ·

2025/02/21

🤗 Upvotes: 21 | cs.CL Authors: Shi Yu, Zhiyuan Liu, Chenyan Xiong Title: Craw4LLM: Efficient Web Crawling for LLM Pretraining Arxiv: http://arxiv.org/abs/2502.13347v1 Abstract: Web crawl is a main source of large language models' (LLMs) pretraining data, but the majority of crawled web pages are discarded in pretraining due to low data quality. This paper presents Crawl4LLM, an

en

25:16

LongPO: Long Context Self-Evolution of Large Language...

Daily Paper Cast ·

2025/02/21

🤗 Upvotes: 19 | cs.CL, cs.LG Authors: Guanzheng Chen, Xin Li, Michael Qizhe Shieh, Lidong Bing Title: LongPO: Long Context Self-Evolution of Large Language Models through Short-to-Long Preference Optimization Arxiv: http://arxiv.org/abs/2502.13922v2 Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities through pretraining and alignment. However,

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1,967 results

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