Papers
Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning
Fengyu Gao, Ruida Zhou, Tianhao Wang et al.
How to Find the Exact Pareto Front for Multi-Objective MDPs?
Yining Li, Peizhong Ju, Ness Shroff
Neural Spacetimes for DAG Representation Learning
Haitz Sáez de Ocáriz Borde, Anastasis Kratsios, Marc T. Law et al.
Inference-Aware Fine-Tuning for Best-of-N Sampling in Large Language Models
Yinlam Chow, Guy Tennenholtz, Izzeddin Gur et al.
DeFT: Decoding with Flash Tree-attention for Efficient Tree-structured LLM Inference
Jinwei Yao, Kaiqi Chen, Kexun Zhang et al.
Variational Search Distributions
Daniel M. Steinberg, Rafael Oliveira, Cheng Soon Ong et al.
Doubly robust identification of treatment effects from multiple environments
Piersilvio De Bartolomeis, Julia Kostin, Javier Abad et al.
Revisiting Random Walks for Learning on Graphs
Jinwoo Kim, Olga Zaghen, Ayhan Suleymanzade et al.
Generalizable Motion Planning via Operator Learning
Sharath Matada, Luke Bhan, Yuanyuan Shi et al.
Revisiting Source-Free Domain Adaptation: a New Perspective via Uncertainty Control
Gezheng Xu, Hui Guo, Li Yi et al.
NetFormer: An interpretable model for recovering dynamical connectivity in neuronal population dynamics
Ziyu Lu, Wuwei Zhang, Trung Le et al.
Block Verification Accelerates Speculative Decoding
Ziteng Sun, Uri Mendlovic, Yaniv Leviathan et al.
Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets
Zhen Liu, Tim Z. Xiao, Weiyang Liu et al.
Kernel-based Optimally Weighted Conformal Time-Series Prediction
Jonghyeok Lee, Chen Xu, Yao Xie
BAMDP Shaping: a Unified Framework for Intrinsic Motivation and Reward Shaping
Aly Lidayan, Michael D Dennis, Stuart Russell
Fine-Tuning Discrete Diffusion Models via Reward Optimization with Applications to DNA and Protein Design
Chenyu Wang, Masatoshi Uehara, Yichun He et al.
EC-DIT: Scaling Diffusion Transformers with Adaptive Expert-Choice Routing
Haotian Sun, Tao Lei, Bowen Zhang et al.
Self-Improving Robust Preference Optimization
Eugene Choi, Arash Ahmadian, Matthieu Geist et al.
Improved Diffusion-based Generative Model with Better Adversarial Robustness
Zekun Wang, Mingyang Yi, Shuchen Xue et al.
PWM: Policy Learning with Multi-Task World Models
Ignat Georgiev, Varun Giridhar, Nicklas Hansen et al.
The Semantic Hub Hypothesis: Language Models Share Semantic Representations Across Languages and Modalities
Zhaofeng Wu, Xinyan Velocity Yu, Dani Yogatama et al.
AssembleFlow: Rigid Flow Matching with Inertial Frames for Molecular Assembly
Hongyu Guo, Yoshua Bengio, Shengchao Liu
Self-MoE: Towards Compositional Large Language Models with Self-Specialized Experts
Junmo Kang, Leonid Karlinsky, Hongyin Luo et al.