Most Cited ICLR "selective knowledge removal" Papers

Neural Active Learning Beyond Bandits

Near-Exact Privacy Amplification for Matrix Mechanisms

Christopher Choquette-Choo, Arun Ganesh, Saminul Haque et al.

Confidential-DPproof: Confidential Proof of Differentially Private Training

Ali Shahin Shamsabadi, Gefei Tan, Tudor Cebere et al.

Feature emergence via margin maximization: case studies in algebraic tasks

Depen Morwani, Benjamin Edelman, Costin-Andrei Oncescu et al.

Looking into User’s Long-term Interests through the Lens of Conservative Evidential Learning

Dingrong Wang, Krishna Neupane, Ervine Zheng et al.

Quantifying Network Similarity using Graph Cumulants

Gecia Bravo-Hermsdorff, Lee M. Gunderson, Pierre-André Maugis et al.

TopoLM: brain-like spatio-functional organization in a topographic language model

Neil Rathi, Johannes Mehrer, Badr AlKhamissi et al.

Cross-Modal Contextualized Diffusion Models for Text-Guided Visual Generation and Editing

Ling Yang, Zhilong Zhang, Zhaochen Yu et al.

SSOLE: Rethinking Orthogonal Low-rank Embedding for Self-Supervised Learning

Lun Huang, Qiang Qiu, Guillermo Sapiro

Large Convolutional Model Tuning via Filter Subspace

Wei Chen, Zichen Miao, Qiang Qiu

SWE-bench: Can Language Models Resolve Real-world Github Issues?

Carlos E Jimenez, John Yang, Alexander Wettig et al.

Bridging and Modeling Correlations in Pairwise Data for Direct Preference Optimization

Yuxin Jiang, Bo Huang, Yufei Wang et al.

COLLIE: Systematic Construction of Constrained Text Generation Tasks

Shunyu Yao, Howard Chen, Austin Hanjie et al.

Goodhart's Law in Reinforcement Learning

Jacek Karwowski, Oliver Hayman, Xingjian Bai et al.

DPaI: Differentiable Pruning at Initialization with Node-Path Balance Principle

Lichuan Xiang, Quan Nguyen-Tri, Lan-Cuong Nguyen et al.

FedHyper: A Universal and Robust Learning Rate Scheduler for Federated Learning with Hypergradient Descent

Ziyao Wang, Jianyu Wang, Ang Li

Langevin Monte Carlo for strongly log-concave distributions: Randomized midpoint revisited

LU YU, Avetik Karagulyan, Arnak Dalalyan

Tailoring Mixup to Data for Calibration

Quentin Bouniot, Pavlo Mozharovskyi, Florence d'Alché-Buc

DIAGNOSIS: Detecting Unauthorized Data Usages in Text-to-image Diffusion Models

Zhenting Wang, Chen Chen, Lingjuan Lyu et al.

On Evaluating the Durability of Safeguards for Open-Weight LLMs

Xiangyu Qi, Boyi Wei, Nicholas Carlini et al.

LeanVec: Searching vectors faster by making them fit

Ishwar Bhati, Cecilia Aguerrebere, Mark Hildebrand et al.

Efficient Dictionary Learning with Switch Sparse Autoencoders

Anish Mudide, Josh Engels, Eric Michaud et al.

Rationalizing and Augmenting Dynamic Graph Neural Networks

Guibin Zhang, Yiyan Qi, Ziyang Cheng et al.

Estimating Shape Distances on Neural Representations with Limited Samples

Dean Pospisil, Brett Larsen, Sarah Harvey et al.

A Branching Decoder for Set Generation

Zixian Huang, Gengyang Xiao, Yu Gu et al.

Maintaining Structural Integrity in Parameter Spaces for Parameter Efficient Fine-tuning

Chongjie Si, Xuehui Wang, Xue Yang et al.

Personalize Segment Anything Model with One Shot

Renrui Zhang, Zhengkai Jiang, Ziyu Guo et al.

Evidential Learning-based Certainty Estimation for Robust Dense Feature Matching

Lile Cai, Chuan Sheng Foo, Xun Xu et al.

Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Tasks

Murtaza Dalal, Tarun Chiruvolu, Devendra Chaplot et al.

Matrix Manifold Neural Networks++

Xuan Son Nguyen, Yang, Aymeric Histace

Policy Design in Long-run Welfare Dynamics

Jiduan Wu, Rediet Abebe, Moritz Hardt et al.

On the Markov Property of Neural Algorithmic Reasoning: Analyses and Methods

Montgomery Bohde, Meng Liu, Alexandra Saxton et al.

$\pi$2vec: Policy Representation with Successor Features

Gianluca Scarpellini, Ksenia Konyushkova, Claudio Fantacci et al.

SPA-BENCH: A COMPREHENSIVE BENCHMARK FOR SMARTPHONE AGENT EVALUATION

Jingxuan Chen, Derek Yuen, Bin Xie et al.

Learning to reconstruct signals from binary measurements alone

Laurent Jacques, Julián Tachella

Towards Understanding Sycophancy in Language Models

Mrinank Sharma, Meg Tong, Tomek Korbak et al.

ADDP: Learning General Representations for Image Recognition and Generation with Alternating Denoising Diffusion Process

Changyao Tian, Chenxin Tao, Jifeng Dai et al.

Global Optimality for Non-linear Constrained Restoration Problems via Invexity

Samuel Pinilla, Jeyan Thiyagalingam

Enhanced Face Recognition using Intra-class Incoherence Constraint

Yuanqing Huang, Yinggui Wang, Le Yang et al.

Where We Have Arrived in Proving the Emergence of Sparse Interaction Primitives in DNNs

Qihan Ren, Jiayang Gao, Wen Shen et al.

From Bricks to Bridges: Product of Invariances to Enhance Latent Space Communication

Irene Cannistraci, Luca Moschella, Marco Fumero et al.

DeeperForward: Enhanced Forward-Forward Training for Deeper and Better Performance

Liang Sun, Yang Zhang, Weizhao He et al.

CLaM-TTS: Improving Neural Codec Language Model for Zero-Shot Text-to-Speech

Jaehyeon Kim, Keon Lee, Seungjun Chung et al.

SVBench: A Benchmark with Temporal Multi-Turn Dialogues for Streaming Video Understanding

Zhenyu Yang, Yuhang Hu, Zemin Du et al.

Spherical Tree-Sliced Wasserstein Distance

Viet-Hoang Tran, Thanh Chu, Minh-Khoi Nguyen-Nhat et al.

Disentangled Representation Learning with the Gromov-Monge Gap

Théo Uscidda, Luca Eyring, Karsten Roth et al.

Towards Unified Human Motion-Language Understanding via Sparse Interpretable Characterization

guangtao lyu, Chenghao Xu, Jiexi Yan et al.

Efficient Low-Bit Quantization with Adaptive Scales for Multi-Task Co-Training

Boyu Liu, Haoyu Huang, Linlin Yang et al.

Batched Low-Rank Adaptation of Foundation Models

Yeming Wen, Swarat Chaudhuri

Regularizing Energy among Training Samples for Out-of-Distribution Generalization

Yiting Chen, Qitian Wu, Junchi Yan

To Clip or not to Clip: the Dynamics of SGD with Gradient Clipping in High-Dimensions

Noah Marshall, Ke Liang Xiao, Atish Agarwala et al.

Locality Alignment Improves Vision-Language Models

Ian Covert, Tony Sun, James Y Zou et al.

Statistical Advantages of Perturbing Cosine Router in Mixture of Experts

Huy Nguyen, Pedram Akbarian Saravi, Trang Pham et al.

Prompting Fairness: Integrating Causality to Debias Large Language Models

Jingling Li, Zeyu Tang, Xiaoyu Liu et al.

Manifold Diffusion Fields

Ahmed Elhag, Ahmed Elhag, Yuyang Wang et al.

Language Control Diffusion: Efficiently Scaling through Space, Time, and Tasks

David Bell, Yujie Lu, Shinda Huang et al.

COCO-Periph: Bridging the Gap Between Human and Machine Perception in the Periphery

Anne Harrington, Vasha DuTell, Mark Hamilton et al.

Dynamic Negative Guidance of Diffusion Models

Felix Koulischer, Johannes Deleu, Gabriel Raya et al.

Bilinear MLPs enable weight-based mechanistic interpretability

Michael Pearce, Thomas Dooms, Alice Rigg et al.

Super(ficial)-alignment: Strong Models May Deceive Weak Models in Weak-to-Strong Generalization

Wenkai Yang, Shiqi Shen, Guangyao Shen et al.

FeatUp: A Model-Agnostic Framework for Features at Any Resolution

Stephanie Fu, Mark Hamilton, Laura E. Brandt et al.

SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis

Dustin Podell, Zion English, Kyle Lacey et al.

Language Modeling Is Compression

Gregoire Deletang, Anian Ruoss, Paul-Ambroise Duquenne et al.

PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization

Xinyuan Wang, Chenxi Li, Zhen Wang et al.

Demystifying Linear MDPs and Novel Dynamics Aggregation Framework

Joongkyu Lee, Min-hwan Oh

Generative Judge for Evaluating Alignment

Junlong Li, Shichao Sun, Weizhe Yuan et al.

Training-Free Diffusion Model Alignment with Sampling Demons

Po-Hung Yeh, Kuang-Huei Lee, Jun-Cheng Chen

MINT: Evaluating LLMs in Multi-turn Interaction with Tools and Language Feedback

Xingyao Wang, Zihan Wang, Jiateng Liu et al.

Revisiting Data Augmentation in Deep Reinforcement Learning

Jianshu Hu, Yunpeng Jiang, Paul Weng

Waxing-and-Waning: a Generic Similarity-based Framework for Efficient Self-Supervised Learning

Sheng Li, Chao Wu, Ao Li et al.

Parsing neural dynamics with infinite recurrent switching linear dynamical systems

Victor Geadah, International Brain Laboratory, Jonathan Pillow

DisenBooth: Identity-Preserving Disentangled Tuning for Subject-Driven Text-to-Image Generation

Hong Chen, Yipeng Zhang, Simin Wu et al.

Plug-and-Play Posterior Sampling under Mismatched Measurement and Prior Models

Marien Renaud, Jiaming Liu, Valentin De Bortoli et al.

LDAdam: Adaptive Optimization from Low-Dimensional Gradient Statistics

Thomas Robert, Mher Safaryan, Ionut-Vlad Modoranu et al.

Sample-Efficient Quality-Diversity by Cooperative Coevolution

Ke Xue, Ren-Jian Wang, Pengyi Li et al.

Score-based generative models break the curse of dimensionality in learning a family of sub-Gaussian distributions

Frank Cole, Yulong Lu

Self-Normalized Resets for Plasticity in Continual Learning

Vivek Farias, Adam Jozefiak

Learning Performance-Improving Code Edits

Alexander Shypula, Aman Madaan, Yimeng Zeng et al.

Navigating Dataset Documentations in AI: A Large-Scale Analysis of Dataset Cards on HuggingFace

Xinyu Yang, Victor Weixin Liang, James Y Zou

Parameter and Memory Efficient Pretraining via Low-rank Riemannian Optimization

Zhanfeng Mo, Long-Kai Huang, Sinno Jialin Pan

Training on the Test Task Confounds Evaluation and Emergence

Ricardo Dominguez-Olmedo, Florian Eddie Dorner, Moritz Hardt

Differentiable Learning of Generalized Structured Matrices for Efficient Deep Neural Networks

Changwoo Lee, Hun-Seok Kim

Long-tailed Diffusion Models with Oriented Calibration

Tianjiao Zhang, Huangjie Zheng, Jiangchao Yao et al.

Talk like a Graph: Encoding Graphs for Large Language Models

Bahare Fatemi, Jonathan Halcrow, Bryan Perozzi

COME: Test-time Adaption by Conservatively Minimizing Entropy

Qingyang Zhang, Yatao Bian, Xinke Kong et al.

Mixture of LoRA Experts

xun wu, Shaohan Huang, Furu Wei

Large Brain Model for Learning Generic Representations with Tremendous EEG Data in BCI

Wei-Bang Jiang, Liming Zhao, Bao-liang Lu

Oracle efficient truncated statistics

Konstantinos Karatapanis, Vasilis Kontonis, Christos Tzamos

SaLoRA: Safety-Alignment Preserved Low-Rank Adaptation

Mingjie Li, Wai Man Si, Michael Backes et al.

Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning

Geraud Nangue Tasse, Devon Jarvis, Steven James et al.

Conformalized Interactive Imitation Learning: Handling Expert Shift and Intermittent Feedback

Michelle Zhao, Henny Admoni, Reid Simmons et al.

A Computational Framework for Modeling Emergence of Color Vision in the Human Brain

Atsunobu Kotani, Yi-Ren Ng

Understanding Convergence and Generalization in Federated Learning through Feature Learning Theory

Wei Huang, Ye Shi, Zhongyi Cai et al.

Unsupervised Multiple Kernel Learning for Graphs via Ordinality Preservation

Yan Sun, Stanley Kok

Learning model uncertainty as variance-minimizing instance weights

Nishant Jain, Karthikeyan Shanmugam, Pradeep Shenoy

Proving Test Set Contamination in Black-Box Language Models

Yonatan Oren, Nicole Meister, Niladri Chatterji et al.

Leveraging Flatness to Improve Information-Theoretic Generalization Bounds for SGD

Ze Peng, Jian Zhang, Yisen Wang et al.

Building Cooperative Embodied Agents Modularly with Large Language Models

Hongxin Zhang, Weihua Du, Jiaming Shan et al.

Flaws of ImageNet, Computer Vision's Favourite Dataset

Nikita Kisel, Illia Volkov, Kateřina Hanzelková et al.

Lossy Compression with Pretrained Diffusion Models

jeremy vonderfecht, Feng Liu

Highly Efficient Self-Adaptive Reward Shaping for Reinforcement Learning

Haozhe Ma, Zhengding Luo, Thanh Vinh Vo et al.

SageAttention: Accurate 8-Bit Attention for Plug-and-play Inference Acceleration

Jintao Zhang, Jia wei, Pengle Zhang et al.

Advancing the Lower Bounds: an Accelerated, Stochastic, Second-order Method with Optimal Adaptation to Inexactness

Artem Agafonov, Dmitry Kamzolov, Alexander Gasnikov et al.

Efficient Continual Finite-Sum Minimization

Ioannis Mavrothalassitis, Stratis Skoulakis, Leello Dadi et al.

Consistent algorithms for multi-label classification with macro-at-$k$ metrics

Erik Schultheis, Wojciech Kotlowski, Marek Wydmuch et al.

PIN: Prolate Spheroidal Wave Function-based Implicit Neural Representations

Viraj Dhananjaya Bandara Jayasundara Jayasundara Mudiyanselage, Heng Zhao, Demetrio Labate et al.

Role of Locality and Weight Sharing in Image-Based Tasks: A Sample Complexity Separation between CNNs, LCNs, and FCNs

Aakash Sunil Lahoti, Stefani Karp, Ezra Winston et al.

Attention-Guided Contrastive Role Representations for Multi-agent Reinforcement Learning

Zican Hu, Zongzhang Zhang, Huaxiong Li et al.

Extendable and Iterative Structure Learning Strategy for Bayesian Networks

Hamid Kalantari, Russell Greiner, Pouria Ramazi

Transformers Provably Solve Parity Efficiently with Chain of Thought

Juno Kim, Taiji Suzuki

Bootstrapping Variational Information Pursuit with Large Language and Vision Models for Interpretable Image Classification

Aditya Chattopadhyay, Kwan Ho Ryan Chan, Rene Vidal

Orbit-Equivariant Graph Neural Networks

Matthew Morris, Bernardo Grau, Ian Horrocks

Generalized Behavior Learning from Diverse Demonstrations

Varshith Sreeramdass, Rohan Paleja, Letian Chen et al.

Simple Minimax Optimal Byzantine Robust Algorithm for Nonconvex Objectives with Uniform Gradient Heterogeneity

Tomoya Murata, Kenta Niwa, Takumi Fukami et al.

Bridging Vision and Language Spaces with Assignment Prediction

Jungin Park, Jiyoung Lee, Kwanghoon Sohn

ILLUSION: Unveiling Truth with a Comprehensive Multi-Modal, Multi-Lingual Deepfake Dataset

Kartik Thakral, Rishabh Ranjan, Akanksha Singh et al.

Subtractive Mixture Models via Squaring: Representation and Learning

Lorenzo Loconte, Aleksanteri Sladek, Stefan Mengel et al.

MVSFormer++: Revealing the Devil in Transformer's Details for Multi-View Stereo

chenjie cao, xinlin ren, Yanwei Fu

RuAG: Learned-rule-augmented Generation for Large Language Models

Yudi Zhang, Pei Xiao, Lu Wang et al.

Video Decomposition Prior: Editing Videos Layer by Layer

Gaurav Shrivastava, Ser-Nam Lim, Abhinav Shrivastava

Momentum Benefits Non-iid Federated Learning Simply and Provably

Ziheng Cheng, Xinmeng Huang, Pengfei Wu et al.

L2P-MIP: Learning to Presolve for Mixed Integer Programming

Chang Liu, Zhichen Dong, Haobo Ma et al.

Learning Planning Abstractions from Language

Weiyu Liu, Geng Chen, Joy Hsu et al.

MOFI: Learning Image Representations from Noisy Entity Annotated Images

Wentao Wu, Aleksei Timofeev, Chen Chen et al.

What Matters to You? Towards Visual Representation Alignment for Robot Learning

Thomas Tian, Chenfeng Xu, Masayoshi Tomizuka et al.

A Data-Driven Measure of Relative Uncertainty for Misclassification Detection

Eduardo Dadalto Câmara Gomes, Marco Romanelli, Georg Pichler et al.

Improving Deep Regression with Tightness

Shihao Zhang, Yuguang Yan, Angela Yao

GSE: Group-wise Sparse and Explainable Adversarial Attacks

Shpresim Sadiku, Moritz Wagner, Sebastian Pokutta

Symmetric Neural-Collapse Representations with Supervised Contrastive Loss: The Impact of ReLU and Batching

Ganesh Ramachandra Kini, Vala Vakilian, Tina Behnia et al.

The impact of allocation strategies in subset learning on the expressive power of neural networks

Ofir Schlisselberg, Ran Darshan

DAFA: Distance-Aware Fair Adversarial Training

Hyungyu Lee, Saehyung Lee, Hyemi Jang et al.

A Multi-Level Framework for Accelerating Training Transformer Models

Longwei Zou, Han Zhang, Yangdong Deng

Leveraging Low-Rank and Sparse Recurrent Connectivity for Robust Closed-Loop Control

Neehal Tumma, Mathias Lechner, Noel Loo et al.

Wavelet Diffusion Neural Operator

Peiyan Hu, Rui Wang, Xiang Zheng et al.

VCR: A Task for Pixel-Level Complex Reasoning in Vision Language Models via Restoring Occluded Text

Tianyu Zhang, Suyuchen Wang, Lu Li et al.

OccProphet: Pushing the Efficiency Frontier of Camera-Only 4D Occupancy Forecasting with an Observer-Forecaster-Refiner Framework

Junliang Chen, Huaiyuan Xu, Yi Wang et al.

Agree to Disagree: Demystifying Homogeneous Deep Ensembles through Distributional Equivalence

Yipei Wang, Xiaoqian Wang

Discovering Clone Negatives via Adaptive Contrastive Learning for Image-Text Matching

Renjie Pan, Jihao Dong, Hua Yang

What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning

Wei Liu, Weihao Zeng, Keqing He et al.

Mitigating Reward Over-Optimization in RLHF via Behavior-Supported Regularization

Juntao Dai, Taiye Chen, Yaodong Yang et al.

Cycle Consistency Driven Object Discovery

Aniket Rajiv Didolkar, Anirudh Goyal, Yoshua Bengio

FreeNoise: Tuning-Free Longer Video Diffusion via Noise Rescheduling

Haonan Qiu, Menghan Xia, Yong Zhang et al.

From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction

Nima Shoghi, Adeesh Kolluru, John Kitchin et al.

IterComp: Iterative Composition-Aware Feedback Learning from Model Gallery for Text-to-Image Generation

Xinchen Zhang, Ling Yang, Guohao Li et al.

Frequency-Aware Transformer for Learned Image Compression

Han Li, Shaohui Li, Wenrui Dai et al.

A Flexible Generative Model for Heterogeneous Tabular EHR with Missing Modality

Huan He, Yijie Hao, Yuanzhe Xi et al.

Resolution Attack: Exploiting Image Compression to Deceive Deep Neural Networks

Wangjia Yu, Xiaomeng Fu, Qiao Li et al.

On gauge freedom, conservativity and intrinsic dimensionality estimation in diffusion models

Christian Horvat, Jean-Pascal Pfister

Chain-of-Experts: When LLMs Meet Complex Operations Research Problems

Ziyang Xiao, Dongxiang Zhang, Yangjun Wu et al.

Walk the Talk? Measuring the Faithfulness of Large Language Model Explanations

Katie Matton, Robert Ness, John Guttag et al.

ProtPainter: Draw or Drag Protein via Topology-guided Diffusion

Zhengxi Lu, Shizhuo Cheng, Yuru Jiang et al.

Redefining the task of Bioactivity Prediction

Yanwen Huang, Bowen Gao, Yinjun JIA et al.

CtD: Composition through Decomposition in Emergent Communication

Boaz Carmeli, Ron Meir, Yonatan Belinkov

What does automatic differentiation compute for neural networks?

Sejun Park, Sanghyuk Chun, Wonyeol Lee

RDesign: Hierarchical Data-efficient Representation Learning for Tertiary Structure-based RNA Design

Cheng Tan, Yijie Zhang, Zhangyang Gao et al.

Revisit Micro-batch Clipping: Adaptive Data Pruning via Gradient Manipulation

Lun Wang

AlpaGasus: Training a Better Alpaca with Fewer Data

Lichang Chen, Shiyang Li, Jun Yan et al.

Model Risk-sensitive Offline Reinforcement Learning

Gwangpyo Yoo, Honguk Woo

Beyond Squared Error: Exploring Loss Design for Enhanced Training of Generative Flow Networks

Rui Hu, Yifan Zhang, Zhuoran Li et al.

Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders

Emanuele Palumbo, Laura Manduchi, Sonia Laguna et al.

Modulated Phase Diffusor: Content-Oriented Feature Synthesis for Detecting Unknown Objects

Aming Wu, Cheng Deng

Spatio-Temporal Approximation: A Training-Free SNN Conversion for Transformers

Yizhou Jiang, Kunlin Hu, Tianren Zhang et al.

Simple yet Effective Incomplete Multi-view Clustering: Similarity-level Imputation and Intra-view Hybrid-group Prototype Construction

Shengju Yu, Zhibin Dong, Siwei Wang et al.

MMICL: Empowering Vision-language Model with Multi-Modal In-Context Learning

Haozhe Zhao, Zefan Cai, Shuzheng Si et al.

UniCBE: An Uniformity-driven Comparing Based Evaluation Framework with Unified Multi-Objective Optimization

Peiwen Yuan, Shaoxiong Feng, Yiwei Li et al.

BarLeRIa: An Efficient Tuning Framework for Referring Image Segmentation

Yaoming Wang, Li Jin, XIAOPENG ZHANG et al.

Achieving Human Parity in Content-Grounded Datasets Generation

Asaf Yehudai, Boaz Carmeli, Yosi Mass et al.

Personality Alignment of Large Language Models

Minjun Zhu, Yixuan Weng, Linyi Yang et al.

Generating Pragmatic Examples to Train Neural Program Synthesizers

Saujas Vaduguru, Daniel Fried, Yewen Pu

Realistic Evaluation of Semi-supervised Learning Algorithms in Open Environments

Lin-Han Jia, Lan-Zhe Guo, Zhi Zhou et al.

Enhancing Transferable Adversarial Attacks on Vision Transformers through Gradient Normalization Scaling and High-Frequency Adaptation

Zhiyu Zhu, Xinyi Wang, Zhibo Jin et al.

Transport meets Variational Inference: Controlled Monte Carlo Diffusions

Francisco Vargas, Shreyas Padhy, Denis Blessing et al.

UniRestore3D: A Scalable Framework For General Shape Restoration

Yuang Wang, Yujian Zhang, Sida Peng et al.

Adversarially Robust Anomaly Detection through Spurious Negative Pair Mitigation

Hossein Mirzaei Sadeghlou, Mojtaba Nafez, Jafar Habibi et al.

Domain constraints improve risk prediction when outcome data is missing

Sidhika Balachandar, Nikhil Garg, Emma Pierson

Uni-O4: Unifying Online and Offline Deep Reinforcement Learning with Multi-Step On-Policy Optimization

Kun LEI, Zhengmao He, Chenhao Lu et al.

A Probabilistic Framework for Modular Continual Learning

Lazar Valkov, Akash Srivastava, Swarat Chaudhuri et al.

BTR: Binary Token Representations for Efficient Retrieval Augmented Language Models

Qingqing Cao, Sewon Min, Yizhong Wang et al.

MMed-RAG: Versatile Multimodal RAG System for Medical Vision Language Models

Peng Xia, Kangyu Zhu, Haoran Li et al.

Hotspot-Driven Peptide Design via Multi-Fragment Autoregressive Extension

Jiahan Li, Tong Chen, Shitong Luo et al.

SCHEMA: State CHangEs MAtter for Procedure Planning in Instructional Videos

Yulei Niu, Wenliang Guo, Long Chen et al.

Semantic Temporal Abstraction via Vision-Language Model Guidance for Efficient Reinforcement Learning

Tian-Shuo Liu, Xu-Hui Liu, Ruifeng Chen et al.

Enhancing Pre-trained Representation Classifiability can Boost its Interpretability

Learning Multi-Agent Communication from Graph Modeling Perspective

Shengchao Hu, Li Shen, Ya Zhang et al.

Reassessing How to Compare and Improve the Calibration of Machine Learning Models

Muthu Chidambaram, Rong Ge

WizardCoder: Empowering Code Large Language Models with Evol-Instruct

Ziyang Luo, Can Xu, Pu Zhao et al.

An improved analysis of per-sample and per-update clipping in federated learning

Bo Li, Xiaowen Jiang, Mikkel N. Schmidt et al.

Rigid Protein-Protein Docking via Equivariant Elliptic-Paraboloid Interface Prediction

Ziyang Yu, Wenbing Huang, Yang Liu

Coordinate-Aware Modulation for Neural Fields

Joo Chan Lee, Daniel Rho, Seungtae Nam et al.

Solving Homogeneous and Heterogeneous Cooperative Tasks with Greedy Sequential Execution

Shanqi Liu, Dong Xing, Pengjie Gu et al.

Variance-enlarged Poisson Learning for Graph-based Semi-Supervised Learning with Extremely Sparse Labeled Data

Xiong Zhou, Xianming Liu, Hao Yu et al.

Bridging the Gap Between f-divergences and Bayes Hilbert Spaces

Linus Lach, Alexander Fottner, Yarema Okhrin

Zero-Mean Regularized Spectral Contrastive Learning: Implicitly Mitigating Wrong Connections in Positive-Pair Graphs

Xiong Zhou, Xianming Liu, feilong zhang et al.

DeepTAGE: Deep Temporal-Aligned Gradient Enhancement for Optimizing Spiking Neural Networks

Wei Liu, Li Yang, Mingxuan Zhao et al.

SysCaps: Language Interfaces for Simulation Surrogates of Complex Systems

Patrick Emami, Zhaonan Li, Saumya Sinha et al.

Revisit the Open Nature of Open Vocabulary Semantic Segmentation

Qiming Huang, Han Hu, Jianbo Jiao

Mitigating Hallucination in Large Multi-Modal Models via Robust Instruction Tuning

Fuxiao Liu, Kevin Lin, Linjie Li et al.

Multi-Scale Fusion for Object Representation

Rongzhen Zhao, Vivienne Huiling Wang, Juho Kannala et al.

Recognize Any Surgical Object: Unleashing the Power of Weakly-Supervised Data

Jiajie Li, Brian Quaranto, Chenhui Xu et al.

SafeWatch: An Efficient Safety-Policy Following Video Guardrail Model with Transparent Explanations

Zhaorun Chen, Francesco Pinto, Minzhou Pan et al.