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ORCID41st ICML 2024: Vienna, Austria
- Forty-first International Conference on Machine Learning, ICML 2024, Vienna, Austria, July 21-27, 2024. OpenReview.net 2024
Accept (Oral)
- Stephen Zhao, Rob Brekelmans, Alireza Makhzani, Roger Baker Grosse:
Probabilistic Inference in Language Models via Twisted Sequential Monte Carlo. - Edward Hughes, Michael D. Dennis, Jack Parker-Holder, Feryal M. P. Behbahani, Aditi Mavalankar, Yuge Shi, Tom Schaul, Tim Rocktäschel:
Position: Open-Endedness is Essential for Artificial Superhuman Intelligence. - Jesse Farebrother, Jordi Orbay, Quan Vuong, Adrien Ali Taïga, Yevgen Chebotar, Ted Xiao, Alex Irpan, Sergey Levine, Pablo Samuel Castro, Aleksandra Faust, Aviral Kumar, Rishabh Agarwal:
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL. - Da Xiao, Qingye Meng, Shengping Li, Xingyuan Yuan:
Improving Transformers with Dynamically Composable Multi-Head Attention. - Vincent Herrmann, Francesco Faccio, Jürgen Schmidhuber:
Learning Useful Representations of Recurrent Neural Network Weight Matrices. - Fei Liu, Xialiang Tong, Mingxuan Yuan, Xi Lin, Fu Luo, Zhenkun Wang, Zhichao Lu, Qingfu Zhang:
Evolution of Heuristics: Towards Efficient Automatic Algorithm Design Using Large Language Model. - Ziniu Hu, Ahmet Iscen, Aashi Jain, Thomas Kipf, Yisong Yue, David A. Ross, Cordelia Schmid, Alireza Fathi:
SceneCraft: An LLM Agent for Synthesizing 3D Scenes as Blender Code. - Weilin Chen, Ruichu Cai, Zeqin Yang, Jie Qiao, Yuguang Yan, Zijian Li, Zhifeng Hao:
Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning. - Jan E. Gerken, Pan Kessel:
Emergent Equivariance in Deep Ensembles. - Linyuan Gong, Sida Wang, Mostafa Elhoushi, Alvin Cheung:
Evaluation of LLMs on Syntax-Aware Code Fill-in-the-Middle Tasks. - Younghyo Park, Gabriel B. Margolis, Pulkit Agrawal:
Position: Automatic Environment Shaping is the Next Frontier in RL. - Qiankun Zhang, Aocheng Shen, Boyu Zhang, Hanrui Jiang, Bingqian Du:
Online Matching with Stochastic Rewards: Provable Better Bound via Adversarial Reinforcement Learning. - Jessica Dai:
Position: Beyond Personhood: Agency, Accountability, and the Limits of Anthropomorphic Ethical Analysis. - Juno Kim, Taiji Suzuki:
Transformers Learn Nonlinear Features In Context: Nonconvex Mean-field Dynamics on the Attention Landscape. - Weixin Liang, Zachary Izzo, Yaohui Zhang, Haley Lepp, Hancheng Cao, Xuandong Zhao, Lingjiao Chen, Haotian Ye, Sheng Liu, Zhi Huang, Daniel A. McFarland, James Y. Zou:
Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews. - Siqi Miao, Zhiyuan Lu, Mia Liu, Javier M. Duarte, Pan Li:
Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics. - Gerald Woo, Chenghao Liu, Akshat Kumar, Caiming Xiong, Silvio Savarese, Doyen Sahoo:
Unified Training of Universal Time Series Forecasting Transformers. - Lucas Spangher, Allen M. Wang, Andrew Maris, Myles Stapelberg, Viraj Mehta, Alex Saperstein, Stephen Lane-Walsh, Akshata Kishore Moharir, Alessandro Pau, Cristina Rea:
Position: Opportunities Exist for Machine Learning in Magnetic Fusion Energy. - Christian Schlarmann, Naman Deep Singh, Francesco Croce, Matthias Hein:
Robust CLIP: Unsupervised Adversarial Fine-Tuning of Vision Embeddings for Robust Large Vision-Language Models. - Yujie Xing, Xiao Wang, Yibo Li, Hai Huang, Chuan Shi:
Less is More: on the Over-Globalizing Problem in Graph Transformers. - Jiawei Zhao, Zhenyu Zhang, Beidi Chen, Zhangyang Wang, Anima Anandkumar, Yuandong Tian:
GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection. - Charlie Hou, Akshat Shrivastava, Hongyuan Zhan, Rylan Conway, Trang Le, Adithya Sagar, Giulia Fanti, Daniel Lazar:
PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs. - Can Yaras, Peng Wang, Laura Balzano, Qing Qu:
Compressible Dynamics in Deep Overparameterized Low-Rank Learning & Adaptation. - Anka Reuel, Lisa Soder, Benjamin Bucknall, Trond Arne Undheim:
Position: Technical Research and Talent is Needed for Effective AI Governance. - Xin Du, Lixin Xiu, Kumiko Tanaka-Ishii:
Bottleneck-Minimal Indexing for Generative Document Retrieval. - Bob Junyi Zou, Matthew E. Levine, Dessi P. Zaharieva, Ramesh Johari, Emily B. Fox:
Hybrid2 Neural ODE Causal Modeling and an Application to Glycemic Response. - Jiayi Chen, Aidong Zhang:
FedMBridge: Bridgeable Multimodal Federated Learning. - Ryan Liu, Theodore R. Sumers, Ishita Dasgupta, Thomas L. Griffiths:
How do Large Language Models Navigate Conflicts between Honesty and Helpfulness? - Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, Bowen Baker, Leo Gao, Leopold Aschenbrenner, Yining Chen, Adrien Ecoffet, Manas Joglekar, Jan Leike, Ilya Sutskever, Jeffrey Wu:
Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision. - Tianying Ji, Yongyuan Liang, Yan Zeng, Yu Luo, Guowei Xu, Jiawei Guo, Ruijie Zheng, Furong Huang, Fuchun Sun, Huazhe Xu:
ACE: Off-Policy Actor-Critic with Causality-Aware Entropy Regularization. - Tom Wollschläger, Niklas Kemper, Leon Hetzel, Johanna Sommer, Stephan Günnemann:
Expressivity and Generalization: Fragment-Biases for Molecular GNNs. - Sepanta Zeighami, Cyrus Shahabi:
Theoretical Analysis of Learned Database Operations under Distribution Shift through Distribution Learnability. - Shayne Longpre, Sayash Kapoor, Kevin Klyman, Ashwin Ramaswami, Rishi Bommasani, Borhane Blili-Hamelin, Yangsibo Huang, Aviya Skowron, Zheng Xin Yong, Suhas Kotha, Yi Zeng, Weiyan Shi, Xianjun Yang, Reid Southen, Alexander Robey, Patrick Chao, Diyi Yang, Ruoxi Jia, Daniel Kang, Sandy Pentland, Arvind Narayanan, Percy Liang, Peter Henderson:
Position: A Safe Harbor for AI Evaluation and Red Teaming. - Kiarash Banihashem, Samira Goudarzi, MohammadTaghi Hajiaghayi, Peyman Jabbarzade, Morteza Monemizadeh:
A Dynamic Algorithm for Weighted Submodular Cover Problem. - Jiachen T. Wang, Tianji Yang, James Zou, Yongchan Kwon, Ruoxi Jia:
Rethinking Data Shapley for Data Selection Tasks: Misleads and Merits. - Shusheng Xu, Wei Fu, Jiaxuan Gao, Wenjie Ye, Weilin Liu, Zhiyu Mei, Guangju Wang, Chao Yu, Yi Wu:
Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study. - Julien Ferry, Ricardo Fukasawa, Timothée Pascal, Thibaut Vidal:
Trained Random Forests Completely Reveal your Dataset. - Uijeong Jang, Jason D. Lee, Ernest K. Ryu:
LoRA Training in the NTK Regime has No Spurious Local Minima. - Jayesh Singla, Ananye Agarwal, Deepak Pathak:
SAPG: Split and Aggregate Policy Gradients. - Lynn Chua, Badih Ghazi, Pritish Kamath, Ravi Kumar, Pasin Manurangsi, Amer Sinha, Chiyuan Zhang:
How Private are DP-SGD Implementations? - Qianlong Wen, Mingxuan Ju, Zhongyu Ouyang, Chuxu Zhang, Yanfang Ye:
From Coarse to Fine: Enable Comprehensive Graph Self-supervised Learning with Multi-granular Semantic Ensemble. - Aaron Lou, Chenlin Meng, Stefano Ermon:
Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution. - Mohammad Pezeshki, Diane Bouchacourt, Mark Ibrahim, Nicolas Ballas, Pascal Vincent, David Lopez-Paz:
Discovering Environments with XRM. - Ilias Diakonikolas, Mingchen Ma, Lisheng Ren, Christos Tzamos:
Fast Co-Training under Weak Dependence via Stream-Based Active Learning. - Masahiro Kato, Akihiro Oga, Wataru Komatsubara, Ryo Inokuchi:
Active Adaptive Experimental Design for Treatment Effect Estimation with Covariate Choice. - Francesco Paissan, Mirco Ravanelli, Cem Subakan:
Listenable Maps for Audio Classifiers. - Barna Saha, Christopher Ye:
I/O Complexity of Attention, or How Optimal is FlashAttention? - Bairu Hou, Yujian Liu, Kaizhi Qian, Jacob Andreas, Shiyu Chang, Yang Zhang:
Decomposing Uncertainty for Large Language Models through Input Clarification Ensembling. - Allen Tran, Aurélien Bibaut, Nathan Kallus:
Inferring the Long-Term Causal Effects of Long-Term Treatments from Short-Term Experiments. - Ta Duy Nguyen, Alina Ene:
Multiplicative Weights Update, Area Convexity and Random Coordinate Descent for Densest Subgraph Problems. - Manuel Glöckler, Michael Deistler, Christian Dietrich Weilbach, Frank Wood, Jakob H. Macke:
All-in-one simulation-based inference. - Thomas Kleine Buening, Victor Villin, Christos Dimitrakakis:
Environment Design for Inverse Reinforcement Learning. - Jonah Brown-Cohen, Geoffrey Irving, Georgios Piliouras:
Scalable AI Safety via Doubly-Efficient Debate. - Yu Luo, Tianying Ji, Fuchun Sun, Jianwei Zhang, Huazhe Xu, Xianyuan Zhan:
OMPO: A Unified Framework for RL under Policy and Dynamics Shifts. - Chendi Wang, Yuqing Zhu, Weijie J. Su, Yu-Xiang Wang:
Neural Collapse meets Differential Privacy: Curious behaviors of NoisyGD with Near-Perfect Representation Learning. - Ziyad Oulhaj, Mathieu Carrière, Bertrand Michel:
Differentiable Mapper for Topological Optimization of Data Representation. - Wenshuo Li, Xinghao Chen, Han Shu, Yehui Tang, Yunhe Wang:
ExCP: Extreme LLM Checkpoint Compression via Weight-Momentum Joint Shrinking. - Haoran Li, Zicheng Zhang, Wang Luo, Congying Han, Yudong Hu, Tiande Guo, Shichen Liao:
Towards Optimal Adversarial Robust Q-learning with Bellman Infinity-error. - Mina Dalirrooyfard, Konstantin Makarychev, Slobodan Mitrovic:
Pruned Pivot: Correlation Clustering Algorithm for Dynamic, Parallel, and Local Computation Models. - Dongping Chen, Ruoxi Chen, Shilin Zhang, Yaochen Wang, Yinuo Liu, Huichi Zhou, Qihui Zhang, Yao Wan, Pan Zhou, Lichao Sun:
MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language Benchmark. - Qinlin Zhao, Jindong Wang, Yixuan Zhang, Yiqiao Jin, Kaijie Zhu, Hao Chen, Xing Xie:
CompeteAI: Understanding the Competition Dynamics of Large Language Model-based Agents. - Simon Buchholz, Bernhard Schölkopf:
Robustness of Nonlinear Representation Learning. - Mustapha Bounoua, Giulio Franzese, Pietro Michiardi:
SΩI: Score-based O-INFORMATION Estimation. - Uri Sherman, Alon Cohen, Tomer Koren, Yishay Mansour:
Rate-Optimal Policy Optimization for Linear Markov Decision Processes. - Danni Yang, Jiayi Ji, Yiwei Ma, Tianyu Guo, Haowei Wang, Xiaoshuai Sun, Rongrong Ji:
SAM as the Guide: Mastering Pseudo-Label Refinement in Semi-Supervised Referring Expression Segmentation. - Francisco Eiras, Aleksandar Petrov, Bertie Vidgen, Christian Schröder de Witt, Fabio Pizzati, Katherine Elkins, Supratik Mukhopadhyay, Adel Bibi, Botos Csaba, Fabro Steibel, Fazl Barez, Genevieve Smith, Gianluca Guadagni, Jon Chun, Jordi Cabot, Joseph Marvin Imperial, Juan A. Nolazco-Flores, Lori Landay, Matthew Thomas Jackson, Paul Röttger, Philip H. S. Torr, Trevor Darrell, Yong Suk Lee, Jakob N. Foerster:
Position: Near to Mid-term Risks and Opportunities of Open-Source Generative AI. - Di Wu, Wasi Uddin Ahmad, Dejiao Zhang, Murali Krishna Ramanathan, Xiaofei Ma:
Repoformer: Selective Retrieval for Repository-Level Code Completion. - Patrick Esser, Sumith Kulal, Andreas Blattmann, Rahim Entezari, Jonas Müller, Harry Saini, Yam Levi, Dominik Lorenz, Axel Sauer, Frederic Boesel, Dustin Podell, Tim Dockhorn, Zion English, Robin Rombach:
Scaling Rectified Flow Transformers for High-Resolution Image Synthesis. - Sayash Kapoor, Rishi Bommasani, Kevin Klyman, Shayne Longpre, Ashwin Ramaswami, Peter Cihon, Aspen K. Hopkins, Kevin Bankston, Stella Biderman, Miranda Bogen, Rumman Chowdhury, Alex Engler, Peter Henderson, Yacine Jernite, Seth Lazar, Stefano Maffulli, Alondra Nelson, Joelle Pineau, Aviya Skowron, Dawn Song, Victor Storchan, Daniel Zhang, Daniel E. Ho, Percy Liang, Arvind Narayanan:
Position: On the Societal Impact of Open Foundation Models. - Zachary Novack, Julian J. McAuley, Taylor Berg-Kirkpatrick, Nicholas J. Bryan:
DITTO: Diffusion Inference-Time T-Optimization for Music Generation. - Woojin Cho, Minju Jo, Haksoo Lim, Kookjin Lee, Dongeun Lee, Sanghyun Hong, Noseong Park:
Parameterized Physics-informed Neural Networks for Parameterized PDEs. - Yifan Xia, Xianliang Yang, Zichuan Liu, Zhihao Liu, Lei Song, Jiang Bian:
Position: Rethinking Post-Hoc Search-Based Neural Approaches for Solving Large-Scale Traveling Salesman Problems. - Gauthier Guinet, Behrooz Omidvar-Tehrani, Anoop Deoras, Laurent Callot:
Automated Evaluation of Retrieval-Augmented Language Models with Task-Specific Exam Generation. - Ruijie Zheng, Ching-An Cheng, Hal Daumé III, Furong Huang, Andrey Kolobov:
PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control. - Jia Shi, Gautam Rajendrakumar Gare, Jinjin Tian, Siqi Chai, Zhiqiu Lin, Arun Balajee Vasudevan, Di Feng, Francesco Ferroni, Shu Kong:
LCA-on-the-Line: Benchmarking Out of Distribution Generalization with Class Taxonomies. - Tijana Zrnic, Emmanuel J. Candès:
Active Statistical Inference. - Yujia Huang, Adishree Ghatare, Yuanzhe Liu, Ziniu Hu, Qinsheng Zhang, Chandramouli Shama Sastry, Siddharth Gururani, Sageev Oore, Yisong Yue:
Symbolic Music Generation with Non-Differentiable Rule Guided Diffusion. - Zeqian Ju, Yuancheng Wang, Kai Shen, Xu Tan, Detai Xin, Dongchao Yang, Eric Liu, Yichong Leng, Kaitao Song, Siliang Tang, Zhizheng Wu, Tao Qin, Xiangyang Li, Wei Ye, Shikun Zhang, Jiang Bian, Lei He, Jinyu Li, Sheng Zhao:
NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models. - Jiachun Li, Kaining Shi, David Simchi-Levi:
Privacy Preserving Adaptive Experiment Design. - Lingfeng Shen, Aayush Mishra, Daniel Khashabi:
Position: Do pretrained Transformers Learn In-Context by Gradient Descent? - Jessy Lin, Yuqing Du, Olivia Watkins, Danijar Hafner, Pieter Abbeel, Dan Klein, Anca D. Dragan:
Learning to Model the World With Language. - Riley Simmons-Edler, Ryan Paul Badman, Shayne Longpre, Kanaka Rajan:
Position: AI-Powered Autonomous Weapons Risk Geopolitical Instability and Threaten AI Research. - Vassilis Papadopoulos, Jérémie Wenger, Clément Hongler:
Arrows of Time for Large Language Models. - Chengshu Li, Jacky Liang, Andy Zeng, Xinyun Chen, Karol Hausman, Dorsa Sadigh, Sergey Levine, Li Fei-Fei, Fei Xia, Brian Ichter:
Chain of Code: Reasoning with a Language Model-Augmented Code Emulator. - Pratik Rathore, Weimu Lei, Zachary Frangella, Lu Lu, Madeleine Udell:
Challenges in Training PINNs: A Loss Landscape Perspective. - Ryan Greenblatt, Buck Shlegeris, Kshitij Sachan, Fabien Roger:
AI Control: Improving Safety Despite Intentional Subversion. - Bowen Zhao, Hannaneh Hajishirzi, Qingqing Cao:
APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference. - Jost Tobias Springenberg, Abbas Abdolmaleki, Jingwei Zhang, Oliver Groth, Michael Bloesch, Thomas Lampe, Philemon Brakel, Sarah Bechtle, Steven Kapturowski, Roland Hafner, Nicolas Heess, Martin A. Riedmiller:
Offline Actor-Critic Reinforcement Learning Scales to Large Models. - Zach Evans, CJ Carr, Josiah Taylor, Scott H. Hawley, Jordi Pons:
Fast Timing-Conditioned Latent Audio Diffusion. - Kai Zhang, Yi Luan, Hexiang Hu, Kenton Lee, Siyuan Qiao, Wenhu Chen, Yu Su, Ming-Wei Chang:
MagicLens: Self-Supervised Image Retrieval with Open-Ended Instructions. - Max Dupré la Tour, Monika Henzinger, David Saulpic:
Making Old Things New: A Unified Algorithm for Differentially Private Clustering. - Wei Zhang, Chaoqun Wan, Yonggang Zhang, Yiu-ming Cheung, Xinmei Tian, Xu Shen, Jieping Ye:
Interpreting and Improving Large Language Models in Arithmetic Calculation. - Shengsheng Lin, Weiwei Lin, Wentai Wu, Haojun Chen, Junjie Yang:
SparseTSF: Modeling Long-term Time Series Forecasting with *1k* Parameters. - Zijian Liu, Zhengyuan Zhou:
On the Last-Iterate Convergence of Shuffling Gradient Methods. - Bowen Jing, Bonnie Berger, Tommi S. Jaakkola:
AlphaFold Meets Flow Matching for Generating Protein Ensembles. - Sajjad Zarifzadeh, Philippe Liu, Reza Shokri:
Low-Cost High-Power Membership Inference Attacks. - Letian Fu, Gaurav Datta, Huang Huang, William Chung-Ho Panitch, Jaimyn Drake, Joseph Ortiz, Mustafa Mukadam, Mike Lambeta, Roberto Calandra, Ken Goldberg:
A Touch, Vision, and Language Dataset for Multimodal Alignment. - Dora Zhao, Jerone T. A. Andrews, Orestis Papakyriakopoulos, Alice Xiang:
Position: Measure Dataset Diversity, Don't Just Claim It. - Zoe Piran, Michal Klein, James Thornton, Marco Cuturi:
Contrasting Multiple Representations with the Multi-Marginal Matching Gap. - Jiahan Zhang, Qi Wei, Feng Liu, Lei Feng:
Candidate Pseudolabel Learning: Enhancing Vision-Language Models by Prompt Tuning with Unlabeled Data. - Haonan Wang, Qianli Shen, Yao Tong, Yang Zhang, Kenji Kawaguchi:
The Stronger the Diffusion Model, the Easier the Backdoor: Data Poisoning to Induce Copyright BreachesWithout Adjusting Finetuning Pipeline. - Nicholas Carlini, Daniel Paleka, Krishnamurthy Dj Dvijotham, Thomas Steinke, Jonathan Hayase, A. Feder Cooper, Katherine Lee, Matthew Jagielski, Milad Nasr, Arthur Conmy, Eric Wallace, David Rolnick, Florian Tramèr:
Stealing part of a production language model. - Hyunin Lee, Ming Jin, Javad Lavaei, Somayeh Sojoudi:
Pausing Policy Learning in Non-stationary Reinforcement Learning. - Akbir Khan, John Hughes, Dan Valentine, Laura Ruis, Kshitij Sachan, Ansh Radhakrishnan, Edward Grefenstette, Samuel R. Bowman, Tim Rocktäschel, Ethan Perez:
Debating with More Persuasive LLMs Leads to More Truthful Answers. - Sanyam Agarwal, Markus Bläser:
Probabilistic Generating Circuits - Demystified. - Mikel Malagon, Josu Ceberio, José Antonio Lozano:
Self-Composing Policies for Scalable Continual Reinforcement Learning. - Jian Xu, Delu Zeng, John W. Paisley:
Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference. - Feihu Huang:
Optimal Hessian/Jacobian-Free Nonconvex-PL Bilevel Optimization. - Li Sun, Zhenhao Huang, Hao Peng, Yujie Wang, Chunyang Liu, Philip S. Yu:
LSEnet: Lorentz Structural Entropy Neural Network for Deep Graph Clustering. - Dan Kondratyuk, Lijun Yu, Xiuye Gu, José Lezama, Jonathan Huang, Grant Schindler, Rachel Hornung, Vighnesh Birodkar, Jimmy Yan, Ming-Chang Chiu, Krishna Somandepalli, Hassan Akbari, Yair Alon, Yong Cheng, Joshua V. Dillon, Agrim Gupta, Meera Hahn, Anja Hauth, David Hendon, Alonso Martinez, David Minnen, Mikhail Sirotenko, Kihyuk Sohn, Xuan Yang, Hartwig Adam, Ming-Hsuan Yang, Irfan Essa, Huisheng Wang, David A. Ross, Bryan Seybold, Lu Jiang:
VideoPoet: A Large Language Model for Zero-Shot Video Generation. - Yang Jin, Zhicheng Sun, Kun Xu, Kun Xu, Liwei Chen, Hao Jiang, Quzhe Huang, Chengru Song, Yuliang Liu, Di Zhang, Yang Song, Kun Gai, Yadong Mu:
Video-LaVIT: Unified Video-Language Pre-training with Decoupled Visual-Motional Tokenization. - Florian Tramèr, Gautam Kamath, Nicholas Carlini:
Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining. - Ce Liu, Suryansh Kumar, Shuhang Gu, Radu Timofte, Yao Yao, Luc Van Gool:
Stereo Risk: A Continuous Modeling Approach to Stereo Matching. - Zhuanghua Liu, Cheng Chen, Luo Luo, Bryan Kian Hsiang Low:
Zeroth-Order Methods for Constrained Nonconvex Nonsmooth Stochastic Optimization. - Idan Attias, Gintare Karolina Dziugaite, Mahdi Haghifam, Roi Livni, Daniel M. Roy:
Information Complexity of Stochastic Convex Optimization: Applications to Generalization, Memorization, and Tracing. - Yunfan Li, Peng Hu, Dezhong Peng, Jiancheng Lv, Jianping Fan, Xi Peng:
Image Clustering with External Guidance. - Andrew Lee, Xiaoyan Bai, Itamar Pres, Martin Wattenberg, Jonathan K. Kummerfeld, Rada Mihalcea:
A Mechanistic Understanding of Alignment Algorithms: A Case Study on DPO and Toxicity. - Yang Zhang, Zhewei Wei, Ye Yuan, Chongxuan Li, Wenbing Huang:
EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Prediction. - Heting Gao, Kaizhi Qian, Junrui Ni, Chuang Gan, Mark A. Hasegawa-Johnson, Shiyu Chang, Yang Zhang:
Speech Self-Supervised Learning Using Diffusion Model Synthetic Data. - Minyoung Huh, Brian Cheung, Tongzhou Wang, Phillip Isola:
Position: The Platonic Representation Hypothesis. - Liam Collins, Hamed Hassani, Mahdi Soltanolkotabi, Aryan Mokhtari, Sanjay Shakkottai:
Provable Multi-Task Representation Learning by Two-Layer ReLU Neural Networks.