All Papers

In-Context Unlearning: Language Models as Few-Shot Unlearners

Martin Pawelczyk, Seth Neel, Himabindu Lakkaraju

In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering

Sheng Liu, Haotian Ye, Lei Xing et al.

Incorporating Geo-Diverse Knowledge into Prompting for Increased Geographical Robustness in Object Recognition

Kyle Buettner, Sina Malakouti, Xiang Li et al.

Incorporating Information into Shapley Values: Reweighting via a Maximum Entropy Approach

Darya Biparva, Donatello Materassi

Incorporating probabilistic domain knowledge into deep multiple instance learning

Ghadi S. Al Hajj, Aliaksandr Hubin, Chakravarthi Kanduri et al.

Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning

Haobo Song, Haobo SONG, Hao Zhao et al.

Incremental Nuclei Segmentation from Histopathological Images via Future-class Awareness and Compatibility-inspired Distillation

Huyong Wang, Huisi Wu, Jing Qin

Incremental Quasi-Newton Methods with Faster Superlinear Convergence Rates

Zhuanghua Liu, Luo Luo, Bryan Kian Hsiang Low

Incremental Randomized Smoothing Certification

Shubham Dipak Ugare, Tarun Suresh, Debangshu Banerjee et al.

Incremental Residual Concept Bottleneck Models

Chenming Shang, Shiji Zhou, Hengyuan Zhang et al.

Incremental Topological Ordering and Cycle Detection with Predictions

Samuel McCauley, Benjamin Moseley, Aidin Niaparast et al.

In Defense of Lazy Visual Grounding for Open-Vocabulary Semantic Segmentation

Dahyun Kang, Minsu Cho

In defense of parameter sharing for model-compression

Aditya Desai, Anshumali Shrivastava

Independence of Irrelevant Alternatives under the Lens of Pairwise Distortion

Independency Adversarial Learning for Cross-Modal Sound Separation

Zhenkai Lin, Yanli Ji, Yang Yang

Independent-Set Design of Experiments for Estimating Treatment and Spillover Effects under Network Interference

Chencheng Cai, Xu Zhang, Edoardo Airoldi

Indirectly Parameterized Concrete Autoencoders

Alfred Nilsson, Klas Wijk, Sai bharath chandra Gutha et al.

In-distribution Public Data Synthesis with Diffusion Models for Differentially Private Image Classification

Jinseong Park, Yujin Choi, Jaewook Lee

Individual Contributions as Intrinsic Exploration Scaffolds for Multi-agent Reinforcement Learning

Xinran Li, Zifan LIU, Shibo Chen et al.

Individual Fairness in Graph Decomposition

Kamesh Munagala, Govind S. Sankar

Individualized Privacy Accounting via Subsampling with Applications in Combinatorial Optimization

Badih Ghazi, Pritish Kamath, Ravi Kumar et al.

Inducing Clusters Deep Kernel Gaussian Process for Longitudinal Data

Junjie Liang, Weijieying Ren, Sahar Hanifi et al.

Inducing High Energy-Latency of Large Vision-Language Models with Verbose Images

Kuofeng Gao, Yang Bai, Jindong Gu et al.

Inducing Point Operator Transformer: A Flexible and Scalable Architecture for Solving PDEs

Seungjun Lee, TaeIL Oh

iNeMo: Incremental Neural Mesh Models for Robust Class-Incremental Learning

Tom Fischer, Yaoyao Liu, Artur Jesslen et al.

Inertial Algorithm with Dry Fraction and Convolutional Sparse Coding for 3D Localization with Light Field Microscopy

Xiaofan Wang, Zhiyuan Deng, Changle Wang et al.

Inexact Newton-type Methods for Optimisation with Nonnegativity Constraints

Oscar Smee, Fred Roosta

Inf-DiT: Upsampling any-resolution image with memory-efficient diffusion transformer.

Zhuoyi Yang, Heyang Jiang, Wenyi Hong et al.

InferCept: Efficient Intercept Support for Augmented Large Language Model Inference

Reyna Abhyankar, Zijian He, Vikranth Srivatsa et al.

Inference and Learning in Dynamic Decision Networks Using Knowledge Compilation

Gabriele Venturato, Vincent Derkinderen, Pedro Zuidberg Dos Martires et al.

Infer from What You Have Seen Before: Temporally-dependent Classifier for Semi-supervised Video Segmentation

Jiafan Zhuang, Zilei Wang, Yixin Zhang et al.

Inferring Change Points in High-Dimensional Linear Regression via Approximate Message Passing

Gabriel Arpino, Xiaoqi Liu, Ramji Venkataramanan

Inferring Dynamic Networks from Marginals with Iterative Proportional Fitting

Serina Chang, Frederic Koehler, Zhaonan Qu et al.

Inferring the Long-Term Causal Effects of Long-Term Treatments from Short-Term Experiments

Allen Tran, Aurelien Bibaut, Nathan Kallus

InfiAgent-DABench: Evaluating Agents on Data Analysis Tasks

Xueyu Hu, Ziyu Zhao, Shuang Wei et al.

Infinigen Indoors: Photorealistic Indoor Scenes using Procedural Generation

Alexander Raistrick, Lingjie Mei, Karhan Kayan et al.

Infinite-Horizon Distributionally Robust Regret-Optimal Control

Taylan Kargin, Joudi Hajar, Vikrant Malik et al.

Infinite-ID: Identity-preserved Personalization via ID-semantics Decoupling Paradigm

Yi Wu, Ziqiang Li, Heliang Zheng et al.

InfLoRA: Interference-Free Low-Rank Adaptation for Continual Learning

Yan-Shuo Liang, Wu-Jun Li

Influencer Backdoor Attack on Semantic Segmentation

Haoheng Lan, Jindong Gu, Philip Torr et al.

Influential Exemplar Replay for Incremental Learning in Recommender Systems

Xinni Zhang, Yankai Chen, Chenhao Ma et al.

InfMAE: A Foundation Model in The Infrared Modality

Fangcen liu, Chenqiang Gao, Yaming Zhang et al.

InfoBatch: Lossless Training Speed Up by Unbiased Dynamic Data Pruning

Ziheng Qin, Kai Wang, Zangwei Zheng et al.

InfoCon: Concept Discovery with Generative and Discriminative Informativeness

Ruizhe Liu, Qian Luo, Yanchao Yang

InfoNet: Neural Estimation of Mutual Information without Test-Time Optimization

Zhengyang Hu, Song Kang, Qunsong Zeng et al.

InfoNorm: Mutual Information Shaping of Normals for Sparse-View Reconstruction

Xulong Wang, Siyan Dong, Youyi Zheng et al.

Information Bottleneck Analysis of Deep Neural Networks via Lossy Compression

Ivan Butakov, Aleksandr Tolmachev, Sofia Malanchuk et al.

Information Bottleneck Based Data Correction in Continual Learning

Shuai Chen, mingyi zhang, Junge Zhang et al.

Information Complexity of Stochastic Convex Optimization: Applications to Generalization, Memorization, and Tracing

Idan Attias, Gintare Karolina Dziugaite, Mahdi Haghifam et al.

Information Design for Congestion Games with Unknown Demand

Svenja M. Griesbach, Martin Hoefer, Max Klimm et al.