ICLR Papers
6,124 papers found • Page 81 of 123
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.
BadEdit: Backdooring Large Language Models by Model Editing
Yanzhou Li, Tianlin Li, Kangjie Chen et al.
BaDExpert: Extracting Backdoor Functionality for Accurate Backdoor Input Detection
Tinghao Xie, Xiangyu Qi, Ping He et al.
Balancing Act: Constraining Disparate Impact in Sparse Models
Meraj Hashemizadeh, Juan Ramirez, Rohan Sukumaran et al.
Bandits Meet Mechanism Design to Combat Clickbait in Online Recommendation
Thomas Kleine Buening, Aadirupa Saha, Christos Dimitrakakis et al.
Bandits with Replenishable Knapsacks: the Best of both Worlds
Martino Bernasconi, Matteo Castiglioni, Andrea Celli et al.
BarLeRIa: An Efficient Tuning Framework for Referring Image Segmentation
Yaoming Wang, Li Jin, XIAOPENG ZHANG et al.
Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering
Han Zhou, Xingchen Wan, Lev Proleev et al.
Batched Low-Rank Adaptation of Foundation Models
Yeming Wen, Swarat Chaudhuri
Batch normalization is sufficient for universal function approximation in CNNs
Rebekka Burkholz
BatchPrompt: Accomplish more with less
Jianzhe Lin, Maurice Diesendruck, Liang Du et al.
BatteryML: An Open-source Platform for Machine Learning on Battery Degradation
Han Zhang, Xiaofan Gui, Shun Zheng et al.
Bayes Conditional Distribution Estimation for Knowledge Distillation Based on Conditional Mutual Information
Linfeng Ye, Shayan Mohajer Hamidi, Renhao Tan et al.
BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference
Siqi Kou, Lei Gan, Dequan Wang et al.
Bayesian Bi-clustering of Neural Spiking Activity with Latent Structures
Ganchao Wei
Bayesian Coreset Optimization for Personalized Federated Learning
Prateek Chanda, Shrey Modi, Ganesh Ramakrishnan
Bayesian Low-rank Adaptation for Large Language Models
Adam Yang, Maxime Robeyns, Xi Wang et al.
Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation
Konstantin Hess, Valentyn Melnychuk, Dennis Frauen et al.
Bayesian Optimization through Gaussian Cox Process Models for Spatio-temporal Data
Yongsheng Mei, Mahdi Imani, Tian Lan
BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction
Jiangmeng Li, Fei Song, Yifan Jin et al.
Beam Enumeration: Probabilistic Explainability For Sample Efficient Self-conditioned Molecular Design
Jeff Guo, Philippe Schwaller
Beating Price of Anarchy and Gradient Descent without Regret in Potential Games
Iosif Sakos, Stefanos Leonardos, Stelios Stavroulakis et al.
Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference
Haoxuan Li, Chunyuan Zheng, Sihao Ding et al.
Be Careful What You Smooth For: Label Smoothing Can Be a Privacy Shield but Also a Catalyst for Model Inversion Attacks
Lukas Struppek, Dominik Hintersdorf, Kristian Kersting