ICLR 2024 Papers
2,297 papers found • Page 4 of 46
Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators?
Tokio Kajitsuka, Issei Sato
ARGS: Alignment as Reward-Guided Search
Maxim Khanov, Jirayu Burapacheep, Yixuan Li
ARM: Refining Multivariate Forecasting with Adaptive Temporal-Contextual Learning
Jiecheng Lu, Xu Han, Shihao Yang
A ROBUST DIFFERENTIAL NEURAL ODE OPTIMIZER
Panagiotis Theodoropoulos, Guan-Horng Liu, Tianrong Chen et al.
A Semantic Invariant Robust Watermark for Large Language Models
Aiwei Liu, Leyi Pan, Xuming Hu et al.
ASID: Active Exploration for System Identification in Robotic Manipulation
Marius Memmel, Andrew Wagenmaker, Chuning Zhu et al.
A Simple and Effective Pruning Approach for Large Language Models
Mingjie Sun, Zhuang Liu, Anna Bair et al.
A Simple and Scalable Representation for Graph Generation
Yunhui Jang, Seul Lee, Sungsoo Ahn
A Simple Interpretable Transformer for Fine-Grained Image Classification and Analysis
DIPANJYOTI PAUL, Arpita Chowdhury, Xinqi Xiong et al.
A Simple Romance Between Multi-Exit Vision Transformer and Token Reduction
Dongyang Liu, Meina Kan, Shiguang Shan et al.
ASMR: Activation-Sharing Multi-Resolution Coordinate Networks for Efficient Inference
Jason Chun Lok Li, Steven Luo, Le Xu et al.
Assessing Uncertainty in Similarity Scoring: Performance & Fairness in Face Recognition
Jean-Rémy Conti, Stephan CLEMENCON
A Stable, Fast, and Fully Automatic Learning Algorithm for Predictive Coding Networks
Tommaso Salvatori, Yuhang Song, Yordan Yordanov et al.
A Statistical Analysis of Wasserstein Autoencoders for Intrinsically Low-dimensional Data
Saptarshi Chakraborty, Peter Bartlett
A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
Yucen Li, Tim G. J. Rudner, Andrew Gordon Wilson
A Sublinear Adversarial Training Algorithm
Yeqi Gao, Lianke Qin, Zhao Song et al.
A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors
Olivier Laurent, Emanuel Aldea, Gianni Franchi
Asymptotically Free Sketched Ridge Ensembles: Risks, Cross-Validation, and Tuning
Pratik Patil, Daniel LeJeune
A Topological Perspective on Demystifying GNN-Based Link Prediction Performance
Yu Wang, Tong Zhao, Yuying Zhao et al.
Attacking Perceptual Similarity Metrics
Abhijay Ghildyal, Feng Liu
Attention-based Iterative Decomposition for Tensor Product Representation
Taewon Park, inchul choi, Minho Lee
Attention-Guided Contrastive Role Representations for Multi-agent Reinforcement Learning
Zican Hu, Zongzhang Zhang, Huaxiong Li et al.
Attention Satisfies: A Constraint-Satisfaction Lens on Factual Errors of Language Models
Mert Yuksekgonul, Varun Chandrasekaran, Erik Jones et al.
AttEXplore: Attribution for Explanation with model parameters eXploration
Zhiyu Zhu, Huaming Chen, Jiayu Zhang et al.
At Which Training Stage Does Code Data Help LLMs Reasoning?
ma yingwei, Yue Liu, Yue Yu et al.
AUC-CL: A Batchsize-Robust Framework for Self-Supervised Contrastive Representation Learning
Rohan Sharma, Kaiyi Ji, Zhiqiang Xu et al.
AUGCAL: Improving Sim2Real Adaptation by Uncertainty Calibration on Augmented Synthetic Images
Prithvijit Chattopadhyay, Bharat Goyal, Boglarka Ecsedi et al.
AuG-KD: Anchor-Based Mixup Generation for Out-of-Domain Knowledge Distillation
Zihao Tang, Zheqi Lv, Shengyu Zhang et al.
Augmented Bayesian Policy Search
Mahdi Kallel, Debabrota Basu, Riad Akrour et al.
Augmenting Transformers with Recursively Composed Multi-grained Representations
Xiang Hu, Qingyang Zhu, Kewei Tu et al.
A Unified and General Framework for Continual Learning
Zhenyi Wang, Yan Li, Li Shen et al.
A Unified Experiment Design Approach for Cyclic and Acyclic Causal Models
Ehsan Mokhtarian, Saber Salehkaleybar, AmirEmad Ghassami et al.
A Unified Framework for Bayesian Optimization under Contextual Uncertainty
Sebastian Shenghong Tay, Chuan-Sheng Foo, Daisuke Urano et al.
A Unified Sampling Framework for Solver Searching of Diffusion Probabilistic Models
Enshu Liu, Xuefei Ning, Huazhong Yang et al.
A unique M-pattern for micro-expression spotting in long videos
Jinxuan Wang, Shiting Xu, Tong Zhang
AutoCast++: Enhancing World Event Prediction with Zero-shot Ranking-based Context Retrieval
Qi Yan, Raihan Seraj, Jiawei He et al.
AutoChunk: Automated Activation Chunk for Memory-Efficient Deep Learning Inference
Xuanlei Zhao, Shenggan Cheng, Guangyang LU et al.
AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models
Xiaogeng Liu, Nan Xu, Muhao Chen et al.
AutoLoRa: An Automated Robust Fine-Tuning Framework
Xilie Xu, Jingfeng Zhang, Mohan Kankanhalli
Automatic Functional Differentiation in JAX
Min Lin
AutomaTikZ: Text-Guided Synthesis of Scientific Vector Graphics with TikZ
Jonas Belouadi, Anne Lauscher, Steffen Eger
AutoVP: An Automated Visual Prompting Framework and Benchmark
Hsi-Ai Tsao, Lei Hsiung, Pin-Yu Chen et al.
Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference Cost
Yuan Gao, WEIZHONG ZHANG, Wenhan Luo et al.
A Variational Framework for Estimating Continuous Treatment Effects with Measurement Error
Erdun Gao, Howard Bondell, Wei Huang et al.
A Variational Perspective on Solving Inverse Problems with Diffusion Models
Morteza Mardani, Jiaming Song, Jan Kautz et al.
A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables
Xinshuai Dong, Biwei Huang, Ignavier Ng et al.
Backdoor Contrastive Learning via Bi-level Trigger Optimization
Weiyu Sun, Xinyu Zhang, Hao LU et al.
Backdoor Federated Learning by Poisoning Backdoor-Critical Layers
Haomin Zhuang, Mingxian Yu, Hao Wang et al.
Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency
Soumyadeep Pal, Yuguang Yao, Ren Wang et al.
BadChain: Backdoor Chain-of-Thought Prompting for Large Language Models
Zhen Xiang, Fengqing Jiang, Zidi Xiong et al.