2024 Spotlight Papers
531 papers found • Page 10 of 11
Sparse and Structured Hopfield Networks
Saúl Santos, Vlad Niculae, Daniel McNamee et al.
Sparse is Enough in Fine-tuning Pre-trained Large Language Models
Weixi Song, Zuchao Li, Lefei Zhang et al.
Spectrally Transformed Kernel Regression
Runtian Zhai, Rattana Pukdee, Roger Jin et al.
SpikePoint: An Efficient Point-based Spiking Neural Network for Event Cameras Action Recognition
Hongwei Ren, Yue ZHOU, Xiaopeng LIN et al.
Stabilizing Contrastive RL: Techniques for Robotic Goal Reaching from Offline Data
Chongyi Zheng, Benjamin Eysenbach, Homer Walke et al.
Stable Neural Stochastic Differential Equations in Analyzing Irregular Time Series Data
YongKyung Oh, Dongyoung Lim, Sungil Kim
Stack Attention: Improving the Ability of Transformers to Model Hierarchical Patterns
Brian DuSell, David Chiang
StackSight: Unveiling WebAssembly through Large Language Models and Neurosymbolic Chain-of-Thought Decompilation
Weike Fang, Zhejian Zhou, Junzhou He et al.
Stay on Topic with Classifier-Free Guidance
Guillaume Sanchez, Alexander Spangher, Honglu Fan et al.
Stereographic Spherical Sliced Wasserstein Distances
Huy Tran, Yikun Bai, Abihith Kothapalli et al.
Stochastic Controlled Averaging for Federated Learning with Communication Compression
Xinmeng Huang, Ping Li, Xiaoyun Li
Stochastic Interpolants with Data-Dependent Couplings
Michael Albergo, Mark Goldstein, Nicholas Boffi et al.
Stochastic Localization via Iterative Posterior Sampling
Louis Grenioux, Maxence Noble, Marylou Gabrié et al.
Submodular Reinforcement Learning
Manish Prajapat, Mojmir Mutny, Melanie Zeilinger et al.
Subtractive Mixture Models via Squaring: Representation and Learning
Lorenzo Loconte, Aleksanteri Sladek, Stefan Mengel et al.
Sudden Drops in the Loss: Syntax Acquisition, Phase Transitions, and Simplicity Bias in MLMs
Angelica Chen, Ravid Shwartz-Ziv, Kyunghyun Cho et al.
SWAP-NAS: Sample-Wise Activation Patterns for Ultra-fast NAS
Yameng Peng, Andy Song, Haytham Fayek et al.
Symmetric Mean-field Langevin Dynamics for Distributional Minimax Problems
Juno Kim, Kakei Yamamoto, Kazusato Oko et al.
Synaptic Weight Distributions Depend on the Geometry of Plasticity
Roman Pogodin, Jonathan Cornford, Arna Ghosh et al.
SyncDreamer: Generating Multiview-consistent Images from a Single-view Image
Yuan Liu, Cheng Lin, Zijiao Zeng et al.
Tabular Insights, Visual Impacts: Transferring Expertise from Tables to Images
Jun-Peng Jiang, Han-Jia Ye, Leye Wang et al.
Task Adaptation from Skills: Information Geometry, Disentanglement, and New Objectives for Unsupervised Reinforcement Learning
Yucheng Yang, Tianyi Zhou, Qiang HE et al.
TD-MPC2: Scalable, Robust World Models for Continuous Control
Nicklas Hansen, Hao Su, Xiaolong Wang
Tensor Trust: Interpretable Prompt Injection Attacks from an Online Game
Sam Toyer, Olivia Watkins, Ethan Mendes et al.
Testing the Feasibility of Linear Programs with Bandit Feedback
Aditya Gangrade, Aditya Gopalan, Venkatesh Saligrama et al.
Test-Time Degradation Adaptation for Open-Set Image Restoration
Yuanbiao Gou, Haiyu Zhao, Boyun Li et al.
Text2Reward: Reward Shaping with Language Models for Reinforcement Learning
Tianbao Xie, Siheng Zhao, Chen Henry Wu et al.
The Consensus Game: Language Model Generation via Equilibrium Search
Athul Jacob, Yikang Shen, Gabriele Farina et al.
The Effective Horizon Explains Deep RL Performance in Stochastic Environments
Cassidy Laidlaw, Banghua Zhu, Stuart Russell et al.
The False Promise of Imitating Proprietary Language Models
Arnav Gudibande, Eric Wallace, Charlie Snell et al.
The Perception-Robustness Tradeoff in Deterministic Image Restoration
Guy Ohayon, Tomer Michaeli, Michael Elad
Thin-Shell Object Manipulations With Differentiable Physics Simulations
Yian Wang, Juntian Zheng, Zhehuan Chen et al.
Tight Partial Identification of Causal Effects with Marginal Distribution of Unmeasured Confounders
Zhiheng Zhang
Time Travel in LLMs: Tracing Data Contamination in Large Language Models
Shahriar Golchin, Mihai Surdeanu
Time Weaver: A Conditional Time Series Generation Model
Sai Shankar Narasimhan, Shubhankar Agarwal, Oguzhan Akcin et al.
Tool-Augmented Reward Modeling
Lei Li, Yekun Chai, Shuohuan Wang et al.
ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs
Yujia Qin, Shihao Liang, Yining Ye et al.
TorchRL: A data-driven decision-making library for PyTorch
Albert Bou, Matteo Bettini, Sebastian Dittert et al.
Towards Energy Efficient Spiking Neural Networks: An Unstructured Pruning Framework
Xinyu Shi, Jianhao Ding, Zecheng Hao et al.
Towards LLM4QPE: Unsupervised Pretraining of Quantum Property Estimation and A Benchmark
Yehui Tang, Hao Xiong, Nianzu Yang et al.
Towards Meta-Pruning via Optimal Transport
Alexander Theus, Olin Geimer, Friedrich Wicke et al.
Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback
Haolin Liu, Chen-Yu Wei, Julian Zimmert
Towards Reliable and Efficient Backdoor Trigger Inversion via Decoupling Benign Features
Xiong Xu, Kunzhe Huang, Yiming Li et al.
Towards Resource-friendly, Extensible and Stable Incomplete Multi-view Clustering
Shengju Yu, Dong Zhibin, Siwei Wang et al.
Towards Robust Fidelity for Evaluating Explainability of Graph Neural Networks
Xu Zheng, Farhad Shirani, Tianchun Wang et al.
Towards Robust Offline Reinforcement Learning under Diverse Data Corruption
Rui Yang, Han Zhong, Jiawei Xu et al.
Towards Robust Out-of-Distribution Generalization Bounds via Sharpness
Yingtian Zou, Kenji Kawaguchi, Yingnan Liu et al.
Towards Theoretical Understanding of Learning Large-scale Dependent Data via Random Features
Chao Wang, Xin Bing, Xin HE et al.
Towards Unified Multi-granularity Text Detection with Interactive Attention
Xingyu Wan, Chengquan Zhang, Pengyuan Lyu et al.
TRAM: Bridging Trust Regions and Sharpness Aware Minimization
Tom Sherborne, Naomi Saphra, Pradeep Dasigi et al.