2024 Spotlight Papers
531 papers found • Page 2 of 11
Beyond the Norms: Detecting Prediction Errors in Regression Models
Andres Altieri, Marco Romanelli, Georg Pichler et al.
Beyond Worst-case Attacks: Robust RL with Adaptive Defense via Non-dominated Policies
Xiangyu Liu, Chenghao Deng, Yanchao Sun et al.
Bilevel Optimization under Unbounded Smoothness: A New Algorithm and Convergence Analysis
Jie Hao, Xiaochuan Gong, Mingrui Liu
Blending Imitation and Reinforcement Learning for Robust Policy Improvement
Xuefeng Liu, Takuma Yoneda, Rick Stevens et al.
Block Acceleration Without Momentum: On Optimal Stepsizes of Block Gradient Descent for Least-Squares
Liangzu Peng, Wotao Yin
Bounding Box Stability against Feature Dropout Reflects Detector Generalization across Environments
Yang Yang, Wenhai Wang, Zhe Chen et al.
Bounds on Representation-Induced Confounding Bias for Treatment Effect Estimation
Valentyn Melnychuk, Dennis Frauen, Stefan Feuerriegel
Bridging Data Gaps in Diffusion Models with Adversarial Noise-Based Transfer Learning
Xiyu Wang, Baijiong Lin, Daochang Liu et al.
BTR: Binary Token Representations for Efficient Retrieval Augmented Language Models
Qingqing Cao, Sewon Min, Yizhong Wang et al.
By Tying Embeddings You Are Assuming the Distributional Hypothesis
Bertolotti Francesco, Walter Cazzola
CABINET: Content Relevance-based Noise Reduction for Table Question Answering
Sohan Patnaik, Heril Changwal, Milan Aggarwal et al.
CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling
Seyedmorteza Sadat, Jakob Buhmann, Derek Bradley et al.
CAMIL: Context-Aware Multiple Instance Learning for Cancer Detection and Subtyping in Whole Slide Images
olga fourkioti, Matt De Vries, Chris Bakal
Can LLMs Keep a Secret? Testing Privacy Implications of Language Models via Contextual Integrity Theory
Niloofar Mireshghallah, Hyunwoo Kim, Xuhui Zhou et al.
Can Sensitive Information Be Deleted From LLMs? Objectives for Defending Against Extraction Attacks
Vaidehi Ramesh Patil, Peter Hase, Mohit Bansal
CAS: A Probability-Based Approach for Universal Condition Alignment Score
Chunsan Hong, ByungHee Cha, Tae-Hyun Oh
Cascading Reinforcement Learning
Yihan Du, R. Srikant, Wei Chen
Catastrophic Jailbreak of Open-source LLMs via Exploiting Generation
Yangsibo Huang, Samyak Gupta, Mengzhou Xia et al.
Circuit Component Reuse Across Tasks in Transformer Language Models
Jack Merullo, Carsten Eickhoff, Ellie Pavlick
CivRealm: A Learning and Reasoning Odyssey in Civilization for Decision-Making Agents
Siyuan Qi, Shuo Chen, Yexin Li et al.
CLAP: Collaborative Adaptation for Patchwork Learning
Sen Cui, Abudukelimu Wuerkaixi, Weishen Pan et al.
CLIPSelf: Vision Transformer Distills Itself for Open-Vocabulary Dense Prediction
Size Wu, Wenwei Zhang, Lumin Xu et al.
Closing the Gap: Achieving Global Convergence (Last Iterate) of Actor-Critic under Markovian Sampling with Neural Network Parametrization
Mudit Gaur, Amrit Singh Bedi, Di Wang et al.
CO2: Efficient Distributed Training with Full Communication-Computation Overlap
Weigao Sun, Qin Zhen, Weixuan Sun et al.
Code as Reward: Empowering Reinforcement Learning with VLMs
David Venuto, Mohammad Sami Nur Islam, Martin Klissarov et al.
Coeditor: Leveraging Repo-level Diffs for Code Auto-editing
Jiayi Wei, Greg Durrett, Isil Dillig
Complex priors and flexible inference in recurrent circuits with dendritic nonlinearities
Benjamin Lyo, Cristina Savin
Compositional Generative Inverse Design
Tailin Wu, Takashi Maruyama, Long Wei et al.
Concentration Inequalities for General Functions of Heavy-Tailed Random Variables
Shaojie Li, Yong Liu
Confidential-DPproof: Confidential Proof of Differentially Private Training
Ali Shahin Shamsabadi, Gefei Tan, Tudor Cebere et al.
Conformal prediction for multi-dimensional time series by ellipsoidal sets
Chen Xu, Hanyang Jiang, Yao Xie
Conformal Risk Control
Anastasios Angelopoulos, Stephen Bates, Adam Fisch et al.
Confronting Reward Model Overoptimization with Constrained RLHF
Ted Moskovitz, Aaditya Singh, DJ Strouse et al.
Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision
Nan Chen, Zemin Liu, Bryan Hooi et al.
Consistent Multi-Class Classification from Multiple Unlabeled Datasets
Zixi Wei, Senlin Shu, Yuzhou Cao et al.
Constrained Bi-Level Optimization: Proximal Lagrangian Value Function Approach and Hessian-free Algorithm
Wei Yao, Chengming Yu, Shangzhi Zeng et al.
Controlled Text Generation via Language Model Arithmetic
Jasper Dekoninck, Marc Fischer, Luca Beurer-Kellner et al.
Convergence of Bayesian Bilevel Optimization
Shi Fu, Fengxiang He, Xinmei Tian et al.
Convergence of Some Convex Message Passing Algorithms to a Fixed Point
Václav Voráček, Tomáš Werner
Convex Relaxations of ReLU Neural Networks Approximate Global Optima in Polynomial Time
Sungyoon Kim, Mert Pilanci
Coordinate-Aware Modulation for Neural Fields
Joo Chan Lee, Daniel Rho, Seungtae Nam et al.
Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning
Michael Matthews, Michael Beukman, Benjamin Ellis et al.
CrIBo: Self-Supervised Learning via Cross-Image Object-Level Bootstrapping
Tim Lebailly, Thomas Stegmüller, Behzad Bozorgtabar et al.
Critical Learning Periods Emerge Even in Deep Linear Networks
Michael Kleinman, Alessandro Achille, Stefano Soatto
CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity
Aditya Bhatt, Daniel Palenicek, Boris Belousov et al.
Debiased Collaborative Filtering with Kernel-Based Causal Balancing
Haoxuan Li, Chunyuan Zheng, Yanghao Xiao et al.
Decision ConvFormer: Local Filtering in MetaFormer is Sufficient for Decision Making
Jeonghye Kim, Su Young Lee, Woojun Kim et al.
Decoding-time Realignment of Language Models
Tianlin Liu, Shangmin Guo, Leonardo Martins Bianco et al.
Deep Orthogonal Hypersphere Compression for Anomaly Detection
Yunhe Zhang, Yan Sun, Jinyu Cai et al.
Defining Neural Network Architecture through Polytope Structures of Datasets
Sangmin Lee, Abbas Mammadov, Jong Chul YE