Papers
Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn
Hongyao Tang, Johan Obando-Ceron, Pablo Samuel Castro et al.
Robust Offline Reinforcement Learning with Linearly Structured f-Divergence Regularization
Cheng Tang, Zhishuai Liu, Pan Xu
Concentration Distribution Learning from Label Distributions
Jiawei Tang, Yuheng Jia
Investigating the Overlooked Hessian Structure: From CNNs to LLMs
Qian-Yuan Tang, Yufei Gu, Yunfeng Cai et al.
Learning Monotonic Probabilities with a Generative Cost Model
Yongxiang Tang, Yanhua Cheng, Xiaocheng Liu et al.
Learning Single Index Models with Diffusion Priors
Anqi Tang, Youming Chen, Shuchen Xue et al.
Reflection-Window Decoding: Text Generation with Selective Refinement
Zeyu Tang, Zhenhao Chen, Xiangchen Song et al.
Vision-Language Model Selection and Reuse for Downstream Adaptation
Hao-Zhe Tan, Zhi Zhou, Yu-Feng Li et al.
Cradle: Empowering Foundation Agents towards General Computer Control
Weihao Tan, Wentao Zhang, Xinrun Xu et al.
Synthesizing Privacy-Preserving Text Data via Finetuning *without* Finetuning Billion-Scale LLMs
Bowen Tan, Zheng Xu, Eric Xing et al.
WMarkGPT: Watermarked Image Understanding via Multimodal Large Language Models
Songbai Tan, Xuerui Qiu, Yao Shu et al.
BoxLM: Unifying Structures and Semantics of Medical Concepts for Diagnosis Prediction in Healthcare
Yanchao Tan, Hang Lv, Yunfei Zhan et al.
S^2FGL: Spatial Spectral Federated Graph Learning
Zihan Tan, Suyuan Huang, Guancheng Wan et al.
Actor-Critics Can Achieve Optimal Sample Efficiency
Kevin Tan, Wei Fan, Yuting Wei
Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings
Rong-Xi Tan, Ming Chen, Ke Xue et al.
Scalable Equilibrium Sampling with Sequential Boltzmann Generators
Charlie B. Tan, Joey Bose, Chen Lin et al.
FedBEns: One-Shot Federated Learning based on Bayesian Ensemble
Jacopo Talpini, Marco Savi, Giovanni Neglia
Neutral residues: revisiting adapters for model extension
Franck Signe Talla, Edouard Grave, Herve Jegou
Towards Learning to Complete Anything in Lidar
Ayça Takmaz, Cristiano Saltori, Neehar Peri et al.
Exploiting Similarity for Computation and Communication-Efficient Decentralized Optimization
Yuki Takezawa, Xiaowen Jiang, Anton Rodomanov et al.
Distributionally Robust Active Learning for Gaussian Process Regression
Shion Takeno, Yoshito Okura, Yu Inatsu et al.
Instance-Optimal Pure Exploration for Linear Bandits on Continuous Arms
Sho Takemori, Yuhei Umeda, Aditya Gopalan
Physics-Informed Weakly Supervised Learning For Interatomic Potentials
Makoto Takamoto, Viktor Zaverkin, Mathias Niepert
Training a Generally Curious Agent
Fahim Tajwar, Yiding Jiang, Abitha Thankaraj et al.
Selective Response Strategies for GenAI
Boaz Taitler, Omer Ben-Porat