Papers
Adam Exploits ℓ_∞-geometry of Loss Landscape via Coordinate-wise Adaptivity
Shuo Xie, Mohamad Amin Mohamadi, Zhiyuan Li
Discriminator-Guided Embodied Planning for LLM Agent
Haofu Qian, Chenjia Bai, Jiatao Zhang et al.
Beyond Squared Error: Exploring Loss Design for Enhanced Training of Generative Flow Networks
Rui Hu, Yifan Zhang, Zhuoran Li et al.
Perplexed by Perplexity: Perplexity-Based Data Pruning With Small Reference Models
Zachary Ankner, Cody Blakeney, Kartik Sreenivasan et al.
MoDeGPT: Modular Decomposition for Large Language Model Compression
Chi-Heng Lin, Shangqian Gao, James Seale Smith et al.
What Does It Mean to Be a Transformer? Insights from a Theoretical Hessian Analysis
Weronika Ormaniec, Felix Dangel, Sidak Pal Singh
A Non-Contrastive Learning Framework for Sequential Recommendation with Preference-Preserving Profile Generation
Huimin Zeng, Xiaojie Wang, Anoop Jain et al.
ADBM: Adversarial Diffusion Bridge Model for Reliable Adversarial Purification
Xiao Li, Wenxuan Sun, Huanran Chen et al.
PeriodWave: Multi-Period Flow Matching for High-Fidelity Waveform Generation
Sang-Hoon Lee, Ha-Yeong Choi, Seong-Whan Lee
CogVideoX: Text-to-Video Diffusion Models with An Expert Transformer
Zhuoyi Yang, Jiayan Teng, Wendi Zheng et al.
MambaExtend: A Training-Free Approach to Improve Long Context Extension of Mamba
Seyedarmin Azizi, Souvik Kundu, Mohammad Erfan Sadeghi et al.
Selective Label Enhancement Learning for Test-Time Adaptation
Yihao Hu, Congyu Qiao, Xin Geng et al.
Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon
USVSN Sai Prashanth, Alvin Deng, Kyle O'Brien et al.
InverseBench: Benchmarking Plug-and-Play Diffusion Priors for Inverse Problems in Physical Sciences
Hongkai Zheng, Wenda Chu, Bingliang Zhang et al.
Diversity Empowers Intelligence: Integrating Expertise of Software Engineering Agents
Kexun Zhang, Weiran Yao, Zuxin Liu et al.
CrossMPT: Cross-attention Message-passing Transformer for Error Correcting Codes
Seong-Joon Park, Hee-Youl Kwak, Sang-Hyo Kim et al.
Which Tasks Should Be Compressed Together? A Causal Discovery Approach for Efficient Multi-Task Representation Compression
Sha Guo, Jing Chen, Zixuan Hu et al.
Handling Delay in Real-Time Reinforcement Learning
Ivan Anokhin, Rishav Rishav, Matthew Riemer et al.
Decoupling Layout from Glyph in Online Chinese Handwriting Generation
Minsi Ren, Yan-Ming Zhang, yi chen
Unearthing Skill-level Insights for Understanding Trade-offs of Foundation Models
Mazda Moayeri, Vidhisha Balachandran, Varun Chandrasekaran et al.
Learning Task Belief Similarity with Latent Dynamics for Meta-Reinforcement Learning
Menglong Zhang, Fuyuan Qian, Quanying Liu
Large Language Models Often Say One Thing and Do Another
Ruoxi Xu, Hongyu Lin, Xianpei Han et al.
EmbedLLM: Learning Compact Representations of Large Language Models
Richard Zhuang, Tianhao Wu, Zhaojin Wen et al.
Global Convergence in Neural ODEs: Impact of Activation Functions
Tianxiang Gao, Siyuan Sun, Hailiang Liu et al.
Mix-LN: Unleashing the Power of Deeper Layers by Combining Pre-LN and Post-LN
Pengxiang Li, Lu Yin, Shiwei Liu