ICLR Papers
6,124 papers found • Page 14 of 123
Context Clues: Evaluating Long Context Models for Clinical Prediction Tasks on EHR Data
Michael Wornow, Suhana Bedi, Miguel Angel Fuentes Hernandez et al.
ContextGNN: Beyond Two-Tower Recommendation Systems
Yiwen Yuan, Zecheng Zhang, Xinwei He et al.
Context-Parametric Inversion: Why Instruction Finetuning May Not Actually Improve Context Reliance
Sachin Goyal, Christina Baek, Zico Kolter et al.
Context Steering: Controllable Personalization at Inference Time
Zhiyang He, Sashrika Pandey, Mariah Schrum et al.
Contextual Document Embeddings
John X. Morris, Alexander Rush
Contextualizing biological perturbation experiments through language
Menghua (Rachel) Wu, Russell Littman, Jacob Levine et al.
Contextual Self-paced Learning for Weakly Supervised Spatio-Temporal Video Grounding
Akash Kumar, Zsolt Kira, Yogesh S Rawat
Continual Slow-and-Fast Adaptation of Latent Neural Dynamics (CoSFan): Meta-Learning What-How & When to Adapt
Ryan Missel, Linwei Wang
Continuity-Preserving Convolutional Autoencoders for Learning Continuous Latent Dynamical Models from Images
Aiqing Zhu, Yuting Pan, Qianxiao Li
Continuous Autoregressive Modeling with Stochastic Monotonic Alignment for Speech Synthesis
Weiwei Lin, Chenhang HE
Continuous Diffusion for Mixed-Type Tabular Data
Markus Mueller, Kathrin Gruber, Dennis Fok
Continuous Ensemble Weather Forecasting with Diffusion models
Martin Andrae, Tomas Landelius, Joel Oskarsson et al.
Continuous Exposure Learning for Low-light Image Enhancement using Neural ODEs
Donggoo Jung, Daehyun Kim, Tae Hyun Kim
CONTRA: Conformal Prediction Region via Normalizing Flow Transformation
Zhenhan FANG, Aixin Tan, Jian Huang
Contractive Dynamical Imitation Policies for Efficient Out-of-Sample Recovery
Amin Soleimani Abyaneh, Mahrokh Boroujeni, Hsiu-Chin Lin et al.
ContraDiff: Planning Towards High Return States via Contrastive Learning
Yixiang Shan, Zhengbang Zhu, Ting Long et al.
Contrastive Learning from Synthetic Audio Doppelgängers
Manuel Cherep, Nikhil Singh
ControlAR: Controllable Image Generation with Autoregressive Models
Zongming Li, Tianheng Cheng, Shoufa Chen et al.
Controllable Blur Data Augmentation Using 3D-Aware Motion Estimation
Insoo Kim, Hana Lee, Hyong-Euk Lee et al.
Controllable Context Sensitivity and the Knob Behind It
Julian Minder, Kevin Du, Niklas Stoehr et al.
Controllable Generation via Locally Constrained Resampling
Kareem Ahmed, Kai-Wei Chang, Guy Van den Broeck
Controllable Safety Alignment: Inference-Time Adaptation to Diverse Safety Requirements
Jingyu Zhang, Ahmed Elgohary Ghoneim, Ahmed Magooda et al.
Controllable Satellite-to-Street-View Synthesis with Precise Pose Alignment and Zero-Shot Environmental Control
Xianghui Ze, Zhenbo Song, Qiwei Wang et al.
Controllable Unlearning for Image-to-Image Generative Models via $\epsilon$-Constrained Optimization
XiaoHua Feng, Yuyuan Li, Chaochao Chen et al.
Controlled LLM Decoding via Discrete Auto-regressive Biasing
Patrick Pynadath, Ruqi Zhang
Controlling Language and Diffusion Models by Transporting Activations
Pau Rodriguez, Arno Blaas, Michal Klein et al.
Controlling Space and Time with Diffusion Models
Daniel Watson, Saurabh Saxena, Lala Li et al.
Controlling the Fidelity and Diversity of Deep Generative Models via Pseudo Density
Sabine Susstrunk, Mathieu Salzmann, Chen Liu et al.
Control-oriented Clustering of Visual Latent Representation
Han Qi, Haocheng Yin, Heng Yang
ConvCodeWorld: Benchmarking Conversational Code Generation in Reproducible Feedback Environments
Hojae Han, seung-won hwang, Rajhans Samdani et al.
Convergence and Implicit Bias of Gradient Descent on Continual Linear Classification
Hyunji Jung, Hanseul Cho, Chulhee Yun
Convergence of Distributed Adaptive Optimization with Local Updates
Ziheng Cheng, Margalit Glasgow
Convergence of Score-Based Discrete Diffusion Models: A Discrete-Time Analysis
Zikun Zhang, Zixiang Chen, Quanquan Gu
Convergent Privacy Loss of Noisy-SGD without Convexity and Smoothness
Eli Chien, Pan Li
Convex Formulations for Training Two-Layer ReLU Neural Networks
Karthik Prakhya, Tolga Birdal, Alp Yurtsever
COPER: Correlation-based Permutations for Multi-View Clustering
Ran Eisenberg, Jonathan Svirsky, Ofir Lindenbaum
Copyright-Protected Language Generation via Adaptive Model Fusion
Javier Abad, Konstantin Donhauser, Francesco Pinto et al.
Coreset Selection via Reducible Loss in Continual Learning
Ruilin Tong, Yuhang Liu, Javen Qinfeng Shi et al.
Coreset Spectral Clustering
Ben Jourdan, Gregory Schwartzman, Peter Macgregor et al.
CoRNStack: High-Quality Contrastive Data for Better Code Retrieval and Reranking
Tarun Suresh, Revanth Gangi Reddy, Yifei Xu et al.
Correcting the Mythos of KL-Regularization: Direct Alignment without Overoptimization via Chi-Squared Preference Optimization
Audrey Huang, Wenhao Zhan, Tengyang Xie et al.
Correlated Proxies: A New Definition and Improved Mitigation for Reward Hacking
Cassidy Laidlaw, Shivam Singhal, Anca Dragan
Correlating instruction-tuning (in multimodal models) with vision-language processing (in the brain)
SUBBA REDDY OOTA, Akshett Rai Jindal, Ishani Mondal et al.
Correlation and Navigation in the Vocabulary Key Representation Space of Language Models
Letian Peng, Chenyang An, Jingbo Shang
CoTFormer: A Chain of Thought Driven Architecture with Budget-Adaptive Computation Cost at Inference
Amirkeivan Mohtashami, Matteo Pagliardini, Martin Jaggi
Counterfactual Concept Bottleneck Models
Gabriele Dominici, Pietro Barbiero, Francesco Giannini et al.
Counterfactual Generative Modeling with Variational Causal Inference
Yulun Wu, Louis McConnell, Claudia Iriondo
Counterfactual Realizability
Arvind Raghavan, Elias Bareinboim
CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion
Joshua Kazdan, Hao Sun, Jiaqi Han et al.
CR2PQ: Continuous Relative Rotary Positional Query for Dense Visual Representation Learning
Shaofeng Zhang, Qiang Zhou, Sitong Wu et al.