Most Cited ICLR "rule-based reinforcement learning" Papers
6,124 papers found • Page 21 of 31
Conference
Towards a statistical theory of data selection under weak supervision
Germain Kolossov, Andrea Montanari, Pulkit Tandon
BayesPrompt: Prompting Large-Scale Pre-Trained Language Models on Few-shot Inference via Debiased Domain Abstraction
Jiangmeng Li, Fei Song, Yifan Jin et al.
A Stable, Fast, and Fully Automatic Learning Algorithm for Predictive Coding Networks
Tommaso Salvatori, Yuhang Song, Yordan Yordanov et al.
NuwaDynamics: Discovering and Updating in Causal Spatio-Temporal Modeling
Kun Wang, Hao Wu, Yifan Duan et al.
Decoupling Weighing and Selecting for Integrating Multiple Graph Pre-training Tasks
Tianyu Fan, Lirong Wu, Yufei Huang et al.
Democratizing Fine-grained Visual Recognition with Large Language Models
Mingxuan Liu, Subhankar Roy, Wenjing Li et al.
GAFormer: Enhancing Timeseries Transformers Through Group-Aware Embeddings
Jingyun Xiao, Ran Liu, Eva Dyer
UC-NERF: Neural Radiance Field for Under-Calibrated Multi-View Cameras in Autonomous Driving
Kai Cheng, Xiaoxiao Long, Wei Yin et al.
A Topological Perspective on Demystifying GNN-Based Link Prediction Performance
Yu Wang, Tong Zhao, Yuying Zhao et al.
On the Posterior Distribution in Denoising: Application to Uncertainty Quantification
Hila Manor, Tomer Michaeli
Approximately Piecewise E(3) Equivariant Point Networks
Matan Atzmon, Jiahui Huang, Francis Williams et al.
Implicit Maximum a Posteriori Filtering via Adaptive Optimization
Gianluca Bencomo, Jake Snell, Thomas L. Griffiths
On Double Descent in Reinforcement Learning with LSTD and Random Features
David Brellmann, Eloïse Berthier, David Filliat et al.
Functional Bayesian Tucker Decomposition for Continuous-indexed Tensor Data
Shikai Fang, Xin Yu, Zheng Wang et al.
Doubly Robust Proximal Causal Learning for Continuous Treatments
Yong Wu, Yanwei Fu, Shouyan Wang et al.
SaNN: Simple Yet Powerful Simplicial-aware Neural Networks
Sravanthi Gurugubelli, Sundeep Prabhakar Chepuri
DMBP: Diffusion model-based predictor for robust offline reinforcement learning against state observation perturbations
Zhihe Yang, Yunjian Xu
GAIA: a benchmark for General AI Assistants
Grégoire Mialon, Clémentine Fourrier, Thomas Wolf et al.
A Neural Framework for Generalized Causal Sensitivity Analysis
Dennis Frauen, Fergus Imrie, Alicia Curth et al.
Improving Intrinsic Exploration by Creating Stationary Objectives
Roger Creus Castanyer, Joshua Romoff, Glen Berseth
SPTNet: An Efficient Alternative Framework for Generalized Category Discovery with Spatial Prompt Tuning
Hongjun Wang, Sagar Vaze, Kai Han
Retrieval-based Disentangled Representation Learning with Natural Language Supervision
Jiawei Zhou, Xiaoguang Li, Lifeng Shang et al.
Composed Image Retrieval with Text Feedback via Multi-grained Uncertainty Regularization
Yiyang Chen, Zhedong Zheng, Wei Ji et al.
FedDA: Faster Adaptive Gradient Methods for Federated Constrained Optimization
Junyi Li, Feihu Huang, Heng Huang
The importance of feature preprocessing for differentially private linear optimization
Ziteng Sun, Ananda Theertha Suresh, Aditya Krishna Menon
Conditional Instrumental Variable Regression with Representation Learning for Causal Inference
Debo Cheng, Ziqi Xu, Jiuyong Li et al.
Improving the Convergence of Dynamic NeRFs via Optimal Transport
Sameera Ramasinghe, Violetta Shevchenko, Gil Avraham et al.
Sparse Weight Averaging with Multiple Particles for Iterative Magnitude Pruning
Moonseok Choi, Hyungi Lee, Giung Nam et al.
Neuron-Enhanced AutoEncoder Matrix Completion and Collaborative Filtering: Theory and Practice
Jicong Fan, Rui Chen, Zhao Zhang et al.
RECOMBINER: Robust and Enhanced Compression with Bayesian Implicit Neural Representations
Jiajun He, Gergely Flamich, Zongyu Guo et al.
Fake It Till Make It: Federated Learning with Consensus-Oriented Generation
Rui Ye, Yaxin Du, Zhenyang Ni et al.
GraphPulse: Topological representations for temporal graph property prediction
Kiarash Shamsi, Farimah Poursafaei, Shenyang(Andy) Huang et al.
Label-Focused Inductive Bias over Latent Object Features in Visual Classification
Ilmin Kang, HyounYoung Bae, Kangil Kim
Dissecting learning and forgetting in language model finetuning
Xiao Zhang, Ji Wu
Prediction without Preclusion: Recourse Verification with Reachable Sets
Avni Kothari, Bogdan Kulynych, Tsui-Wei Weng et al.
Amortized Network Intervention to Steer the Excitatory Point Processes
Zitao Song, Wendi Ren, Shuang Li
Unconstrained Stochastic CCA: Unifying Multiview and Self-Supervised Learning
James Chapman, Lennie Wells, Ana Lawry Aguila
lpNTK: Better Generalisation with Less Data via Sample Interaction During Learning
Shangmin Guo, YI REN, Stefano Albrecht et al.
Sudden Drops in the Loss: Syntax Acquisition, Phase Transitions, and Simplicity Bias in MLMs
Angelica Chen, Ravid Shwartz-Ziv, Kyunghyun Cho et al.
Don't Trust: Verify -- Grounding LLM Quantitative Reasoning with Autoformalization
Jin Zhou, Charles Staats, Wenda Li et al.
Learning No-Regret Sparse Generalized Linear Models with Varying Observation(s)
Diyang Li, Charles Ling, Zhiqiang Xu et al.
Nevis'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research
Jorg Bornschein, Alexandre Galashov, Ross Hemsley et al.
Protein-ligand binding representation learning from fine-grained interactions
Shikun Feng, Minghao Li, Yinjun JIA et al.
Constrained Decoding for Cross-lingual Label Projection
Duong Le, Yang Chen, Alan Ritter et al.
Source-Free and Image-Only Unsupervised Domain Adaptation for Category Level Object Pose Estimation
Prakhar Kaushik, Aayush Mishra, Adam Kortylewski et al.
ChatEval: Towards Better LLM-based Evaluators through Multi-Agent Debate
Chi-Min Chan, Weize Chen, Yusheng Su et al.
Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni et al.
On Differentially Private Federated Linear Contextual Bandits
Xingyu Zhou, Sayak Ray Chowdhury
Federated Wasserstein Distance
alain rakotomamonjy, Kimia Nadjahi, Liva Ralaivola
Win-Win: Training High-Resolution Vision Transformers from Two Windows
Vincent Leroy, Jerome Revaud, Thomas Lucas et al.
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
Xinyu Tang, Richard Shin, Huseyin Inan et al.
Trajeglish: Traffic Modeling as Next-Token Prediction
Jonah Philion, Xue Bin Peng, Sanja Fidler
KAN: Kolmogorov–Arnold Networks
Ziming Liu, Yixuan Wang, Sachin Vaidya et al.
Cauchy-Schwarz Divergence Information Bottleneck for Regression
Shujian Yu, Xi Yu, Sigurd Løkse et al.
Continuous-Multiple Image Outpainting in One-Step via Positional Query and A Diffusion-based Approach
Shaofeng Zhang, Jinfa Huang, Qiang Zhou et al.
A Primal-Dual Approach to Solving Variational Inequalities with General Constraints
Tatjana Chavdarova, Tong Yang, Matteo Pagliardini et al.
Respect the model: Fine-grained and Robust Explanation with Sharing Ratio Decomposition
Sangyu Han, Yearim Kim, Nojun Kwak
An LLM can Fool Itself: A Prompt-Based Adversarial Attack
Xilie Xu, Keyi Kong, Ning Liu et al.
Outlier-Robust Subsampling Techniques for Persistent Homology
Bernadette J. Stolz
On Penalty Methods for Nonconvex Bilevel Optimization and First-Order Stochastic Approximation
Jeongyeol Kwon, Dohyun Kwon, Stephen Wright et al.
Novel Quadratic Constraints for Extending LipSDP beyond Slope-Restricted Activations
Patricia Pauli, Aaron Havens, Alexandre Araujo et al.
Safe RLHF: Safe Reinforcement Learning from Human Feedback
Juntao Dai, Xuehai Pan, Ruiyang Sun et al.
Steve-Eye: Equipping LLM-based Embodied Agents with Visual Perception in Open Worlds
Sipeng Zheng, jiazheng liu, Yicheng Feng et al.
Towards Faithful Explanations: Boosting Rationalization with Shortcuts Discovery
Linan Yue, Qi Liu, Yichao Du et al.
VDC: Versatile Data Cleanser based on Visual-Linguistic Inconsistency by Multimodal Large Language Models
Zihao Zhu, Mingda Zhang, Shaokui Wei et al.
DataInf: Efficiently Estimating Data Influence in LoRA-tuned LLMs and Diffusion Models
Yongchan Kwon, Eric Wu, Kevin Wu et al.
PubDef: Defending Against Transfer Attacks From Public Models
Chawin Sitawarin, Jaewon Chang, David Huang et al.
Efficient Streaming Language Models with Attention Sinks
Guangxuan Xiao, Yuandong Tian, Beidi Chen et al.
LongLoRA: Efficient Fine-tuning of Long-Context Large Language Models
Yukang Chen, Shengju Qian, Haotian Tang et al.
Training Bayesian Neural Networks with Sparse Subspace Variational Inference
Junbo Li, Zichen Miao, Qiang Qiu et al.
Let's do the time-warp-attend: Learning topological invariants of dynamical systems
Noa Moriel, Matt Ricci, Mor Nitzan
Mol-Instructions: A Large-Scale Biomolecular Instruction Dataset for Large Language Models
Yin Fang, Xiaozhuan Liang, Ningyu Zhang et al.
GeoLLM: Extracting Geospatial Knowledge from Large Language Models
Rohin Manvi, Samar Khanna, Gengchen Mai et al.
Learning Hierarchical World Models with Adaptive Temporal Abstractions from Discrete Latent Dynamics
Christian Gumbsch, Noor Sajid, Georg Martius et al.
On Characterizing the Trade-off in Invariant Representation Learning
Vishnu Boddeti, Sepehr Dehdashtian, Bashir Sadeghi
Llemma: An Open Language Model for Mathematics
Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster et al.
Zeroth-Order Optimization Meets Human Feedback: Provable Learning via Ranking Oracles
Zhiwei Tang, Dmitry Rybin, Tsung-Hui Chang
Adapting and Evaluating Influence-Estimation Methods for Gradient-Boosted Decision Trees
Jonathan Brophy, Zayd Hammoudeh, Daniel Lowd
Neural Ordinary Differential Equations for Modeling Epidemic Spreading
Michalis Vazirgiannis, Chrysoula Kosma, George Panagopoulos et al.
Proximal Policy Gradient Arborescence for Quality Diversity Reinforcement Learning
Sumeet Batra, Bryon Tjanaka, Matthew Fontaine et al.
Improving Non-Transferable Representation Learning by Harnessing Content and Style
Ziming Hong, Zhenyi Wang, Li Shen et al.
The Devil is in the Neurons: Interpreting and Mitigating Social Biases in Language Models
Yan Liu, Yu Liu, Xiaokang Chen et al.
Neural Fourier Transform: A General Approach to Equivariant Representation Learning
Masanori Koyama, Kenji Fukumizu, Kohei Hayashi et al.
Hybrid Sharing for Multi-Label Image Classification
Zihao Yin, Chen Gan, Kelei He et al.
Learning invariant representations of time-homogeneous stochastic dynamical systems
Vladimir Kostic, Pietro Novelli, Riccardo Grazzi et al.
Understanding Transferable Representation Learning and Zero-shot Transfer in CLIP
Zixiang Chen, Yihe Deng, Yuanzhi Li et al.
Complex priors and flexible inference in recurrent circuits with dendritic nonlinearities
Benjamin Lyo, Cristina Savin
Guiding Instruction-based Image Editing via Multimodal Large Language Models
Tsu-Jui Fu, Wenze Hu, Xianzhi Du et al.
Real3D-Portrait: One-shot Realistic 3D Talking Portrait Synthesis
Zhenhui Ye, Tianyun Zhong, Yi Ren et al.
InsertNeRF: Instilling Generalizability into NeRF with HyperNet Modules
Yanqi Bao, Tianyu Ding, Jing Huo et al.
Towards Optimal Regret in Adversarial Linear MDPs with Bandit Feedback
Haolin Liu, Chen-Yu Wei, Julian Zimmert
Lemur: Integrating Large Language Models in Automated Program Verification
Haoze Wu, Clark Barrett, Nina Narodytska
A Simple and Effective Pruning Approach for Large Language Models
Mingjie Sun, Zhuang Liu, Anna Bair et al.
Safety-Tuned LLaMAs: Lessons From Improving the Safety of Large Language Models that Follow Instructions
Federico Bianchi, Mirac Suzgun, Giuseppe Attanasio et al.
Never Train from Scratch: Fair Comparison of Long-Sequence Models Requires Data-Driven Priors
Ido Amos, Jonathan Berant, Ankit Gupta
Adversarial AutoMixup
Huafeng Qin, Xin Jin, Yun Jiang et al.
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization
Dinghuai Zhang, Ricky T. Q. Chen, Chenghao Liu et al.
Leveraging Optimization for Adaptive Attacks on Image Watermarks
Nils Lukas, Abdelrahman Ahmed, Lucas Fenaux et al.
A Lie Group Approach to Riemannian Batch Normalization
Ziheng Chen, Yue Song, Yunmei Liu et al.
Exposing Text-Image Inconsistency Using Diffusion Models
Mingzhen Huang, Shan Jia, Zhou Zhou et al.
FOSI: Hybrid First and Second Order Optimization
Hadar Sivan, Moshe Gabel, Assaf Schuster
Reclaiming the Source of Programmatic Policies: Programmatic versus Latent Spaces
Tales Carvalho, Kenneth Tjhia, Levi Lelis
Learning Multi-Faceted Prototypical User Interests
Nhu-Thuat Tran, Hady W. Lauw
Effective Structural Encodings via Local Curvature Profiles
Lukas Fesser, Melanie Weber
ODICE: Revealing the Mystery of Distribution Correction Estimation via Orthogonal-gradient Update
Liyuan Mao, Haoran Xu, Weinan Zhang et al.
Cascading Reinforcement Learning
Yihan Du, R. Srikant, Wei Chen
A Black-box Approach for Non-stationary Multi-agent Reinforcement Learning
Haozhe Jiang, Qiwen Cui, Zhihan Xiong et al.
ReMasker: Imputing Tabular Data with Masked Autoencoding
Tianyu Du, Luca Melis, Ting Wang
Exploring Weight Balancing on Long-Tailed Recognition Problem
Naoya Hasegawa, Issei Sato
Towards Enhancing Time Series Contrastive Learning: A Dynamic Bad Pair Mining Approach
Xiang Lan, Hanshu Yan, Shenda Hong et al.
Scaling Laws of RoPE-based Extrapolation
Xiaoran Liu, Hang Yan, Chenxin An et al.
Deep Neural Networks Tend To Extrapolate Predictably
Katie Kang, Amrith Setlur, Claire Tomlin et al.
Benign Oscillation of Stochastic Gradient Descent with Large Learning Rate
Miao Lu, Beining Wu, Xiaodong Yang et al.
Towards Generative Abstract Reasoning: Completing Raven’s Progressive Matrix via Rule Abstraction and Selection
Fan Shi, Bin Li, Xiangyang Xue
Davidsonian Scene Graph: Improving Reliability in Fine-grained Evaluation for Text-to-Image Generation
Jaemin Cho, Yushi Hu, Jason Baldridge et al.
DIFFTACTILE: A Physics-based Differentiable Tactile Simulator for Contact-rich Robotic Manipulation
Zilin Si, Gu Zhang, Qingwei Ben et al.
On the Role of Discrete Tokenization in Visual Representation Learning
Tianqi Du, Yifei Wang, Yisen Wang
In-Context Learning Dynamics with Random Binary Sequences
Eric Bigelow, Ekdeep Singh Lubana, Robert Dick et al.
Whittle Index with Multiple Actions and State Constraint for Inventory Management
Chuheng Zhang, Xiangsen Wang, Wei Jiang et al.
MiniLLM: Knowledge Distillation of Large Language Models
Yuxian Gu, Li Dong, Furu Wei et al.
Implicit Neural Representation Inference for Low-Dimensional Bayesian Deep Learning
Panagiotis Dimitrakopoulos, Giorgos Sfikas, Christophoros Nikou
When Scaling Meets LLM Finetuning: The Effect of Data, Model and Finetuning Method
Biao Zhang, Zhongtao Liu, Colin Cherry et al.
CryoGEN: Generative Energy-based Models for Cryogenic Electron Tomography Reconstruction
Yunfei Teng, Yuxuan Ren, Kai Chen et al.
Pessimistic Nonlinear Least-Squares Value Iteration for Offline Reinforcement Learning
Qiwei Di, Heyang Zhao, Jiafan He et al.
EMO: EARTH MOVER DISTANCE OPTIMIZATION FOR AUTO-REGRESSIVE LANGUAGE MODELING
Siyu Ren, Zhiyong Wu, Kenny Zhu
OPTIMAL ROBUST MEMORIZATION WITH RELU NEURAL NETWORKS
Lijia Yu, XIAOSHAN GAO, Lijun Zhang
Stochastic Controlled Averaging for Federated Learning with Communication Compression
Xinmeng Huang, Ping Li, Xiaoyun Li
Boosting Vanilla Lightweight Vision Transformers via Re-parameterization
Zhentao Tan, Xiaodan Li, Yue Wu et al.
Generalization error of spectral algorithms
Maksim Velikanov, Maxim Panov, Dmitry Yarotsky
CrIBo: Self-Supervised Learning via Cross-Image Object-Level Bootstrapping
Tim Lebailly, Thomas Stegmüller, Behzad Bozorgtabar et al.
The Reasonableness Behind Unreasonable Translation Capability of Large Language Model
Tingchen Fu, lemao liu, Deng Cai et al.
Self-Supervised Heterogeneous Graph Learning: a Homophily and Heterogeneity View
YUJIE MO, Feiping Nie, Ping Hu et al.
Chain of Thought Empowers Transformers to Solve Inherently Serial Problems
Zhiyuan Li, Hong Liu, Denny Zhou et al.
Fair Classifiers that Abstain without Harm
Tongxin Yin, Jean-Francois Ton, Ruocheng Guo et al.
Repelling Random Walks
Isaac Reid, Eli Berger, Krzysztof Choromanski et al.
Vision Transformers Need Registers
Timothée Darcet, Maxime Oquab, Julien Mairal et al.
Zero-Shot Continuous Prompt Transfer: Generalizing Task Semantics Across Language Models
Zijun Wu, Yongkang Wu, Lili Mou
Defining Expertise: Applications to Treatment Effect Estimation
Alihan Hüyük, Qiyao Wei, Alicia Curth 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
LipSim: A Provably Robust Perceptual Similarity Metric
Sara Ghazanfari, Alexandre Araujo, Prashanth Krishnamurthy et al.
Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF
Anand Siththaranjan, Cassidy Laidlaw, Dylan Hadfield-Menell
On Accelerating Diffusion-Based Sampling Processes via Improved Integration Approximation
Guoqiang Zhang, Kenta Niwa, W. Bastiaan Kleijn
LightHGNN: Distilling Hypergraph Neural Networks into MLPs for 100x Faster Inference
Yifan Feng, Yihe Luo, Shihui Ying et al.
On Diffusion Modeling for Anomaly Detection
Victor Livernoche, Vineet Jain, Yashar Hezaveh et al.
G$^2$N$^2$ : Weisfeiler and Lehman go grammatical
Jason Piquenot, Aldo Moscatelli, Maxime Berar et al.
Be More Active! Understanding the Differences Between Mean and Sampled Representations of Variational Autoencoders
Lisa Bonheme, Marek Grzes
Meta Inverse Constrained Reinforcement Learning: Convergence Guarantee and Generalization Analysis
Shicheng Liu, Minghui Zhu
Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight
Jiacheng Guo, Minshuo Chen, Huan Wang et al.
Views Can Be Deceiving: Improved SSL Through Feature Space Augmentation
Kimia Hamidieh, Haoran Zhang, Swami Sankaranarayanan et al.
Lie Group Decompositions for Equivariant Neural Networks
Mircea Mironenco, Patrick Forré
Conformal Prediction via Regression-as-Classification
Etash Guha, Shlok Natarajan, Thomas Möllenhoff et al.
$\mathbb{D}^2$ Pruning: Message Passing for Balancing Diversity & Difficulty in Data Pruning
Adyasha Maharana, Prateek Yadav, Mohit Bansal
General Graph Random Features
Isaac Reid, Krzysztof Choromanski, Eli Berger et al.
Privacy-Preserving In-Context Learning for Large Language Models
Tong Wu, Ashwinee Panda, Jiachen (Tianhao) Wang et al.
Perceptual Scales Predicted by Fisher Information Metrics
Jonathan Vacher, Pascal Mamassian
Turning large language models into cognitive models
Marcel Binz, Eric Schulz
Neural Snowflakes: Universal Latent Graph Inference via Trainable Latent Geometries
Haitz Sáez de Ocáriz Borde, Anastasis Kratsios
Towards the Fundamental Limits of Knowledge Transfer over Finite Domains
Qingyue Zhao, Banghua Zhu
Quantifying and Enhancing Multi-modal Robustness with Modality Preference
Zequn Yang, Yake Wei, Ce Liang et al.
Improved Techniques for Training Consistency Models
Yang Song, Prafulla Dhariwal
Modeling Boundedly Rational Agents with Latent Inference Budgets
Athul Jacob, Abhishek Gupta, Jacob Andreas
Understanding Domain Generalization: A Noise Robustness Perspective
Rui Qiao, Bryan Kian Hsiang Low
Equivariant Scalar Fields for Molecular Docking with Fast Fourier Transforms
Bowen Jing, Tommi Jaakkola, Bonnie Berger
Diffusion-TS: Interpretable Diffusion for General Time Series Generation
Xinyu Yuan, Yan Qiao
Towards Seamless Adaptation of Pre-trained Models for Visual Place Recognition
Feng Lu, Lijun Zhang, Xiangyuan Lan et al.
GNNX-BENCH: Unravelling the Utility of Perturbation-based GNN Explainers through In-depth Benchmarking
Mert Kosan, Samidha Verma, Burouj Armgaan et al.
A Benchmark Study on Calibration
Linwei Tao, Younan Zhu, Haolan Guo et al.
Lifting Architectural Constraints of Injective Flows
Peter Sorrenson, Felix Draxler, Armand Rousselot et al.
SOInter: A Novel Deep Energy-Based Interpretation Method for Explaining Structured Output Models
S. Fatemeh Seyyedsalehi, Mahdieh Baghshah, Hamid Rabiee
ModernTCN: A Modern Pure Convolution Structure for General Time Series Analysis
DongHao Luo, Xue Wang
The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning
Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu et al.
Evaluating Large Language Models at Evaluating Instruction Following
Zhiyuan Zeng, Jiatong Yu, Tianyu Gao et al.
Learning Grounded Action Abstractions from Language
Lio Wong, Jiayuan Mao, Pratyusha Sharma et al.
From Sparse to Soft Mixtures of Experts
Joan Puigcerver, Carlos Riquelme Ruiz, Basil Mustafa et al.
iGraphMix: Input Graph Mixup Method for Node Classification
Jongwon Jeong, Hoyeop Lee, Hyui Geon Yoon et al.
Raidar: geneRative AI Detection viA Rewriting
Chengzhi Mao, Carl Vondrick, Hao Wang et al.
THOUGHT PROPAGATION: AN ANALOGICAL APPROACH TO COMPLEX REASONING WITH LARGE LANGUAGE MODELS
Junchi Yu, Ran He, Rex Ying
INViTE: INterpret and Control Vision-Language Models with Text Explanations
Haozhe Chen, Junfeng Yang, Carl Vondrick et al.
Effective pruning of web-scale datasets based on complexity of concept clusters
Amro Kamal, Evgenia Rusak, Kushal Tirumala et al.
Remote Sensing Vision-Language Foundation Models without Annotations via Ground Remote Alignment
Utkarsh Kumar Mall, Cheng Perng Phoo, Meilin Liu et al.
DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks
Kaijie Zhu, Jiaao Chen, Jindong Wang et al.
FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods
Xiaotian Han, Jianfeng Chi, Yu Chen et al.
Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances
Mikhail Khodak, Edmond Chow, Nina Balcan et al.
Self-supervised Pocket Pretraining via Protein Fragment-Surroundings Alignment
Bowen Gao, Yinjun JIA, Yuanle Mo et al.
Solving Diffusion ODEs with Optimal Boundary Conditions for Better Image Super-Resolution
Yiyang Ma, Huan Yang, Wenhan Yang et al.
Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning
Ruizhe Shi, Yuyao Liu, Yanjie Ze et al.
MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework
Sirui Hong, Mingchen Zhuge, Jonathan Chen et al.
Hard-Constrained Deep Learning for Climate Downscaling
Paula Harder, Alex Hernandez-Garcia, Venkatesh Ramesh et al.
Efficient Dynamics Modeling in Interactive Environments with Koopman Theory
Arnab Mondal, Siba Smarak Panigrahi, Sai Rajeswar et al.
Scalable Diffusion for Materials Generation
Sherry Yang, Kwanghwan Cho, Amil Merchant et al.
MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process
Xinyao Fan, Yueying Wu, Chang XU et al.
HAZARD Challenge: Embodied Decision Making in Dynamically Changing Environments
Qinhong Zhou, Sunli Chen, Yisong Wang et al.
A Study of Bayesian Neural Network Surrogates for Bayesian Optimization
Yucen Li, Tim G. J. Rudner, Andrew Gordon Wilson
Prediction Error-based Classification for Class-Incremental Learning
Michał Zając, Tinne Tuytelaars, Gido M van de Ven
I2VControl-Camera: Precise Video Camera Control with Adjustable Motion Strength
Wanquan Feng, Jiawei Liu, Pengqi Tu et al.
Noise-conditioned Energy-based Annealed Rewards (NEAR): A Generative Framework for Imitation Learning from Observation
Anish Abhijit Diwan, Julen Urain, Jens Kober et al.
Learning to Contextualize Web Pages for Enhanced Decision Making by LLM Agents
Dongjun Lee, Juyong Lee, Kyuyoung Kim et al.
Universal Image Restoration Pre-training via Degradation Classification
Jiakui Hu, Lujia Jin, Zhengjian Yao et al.
Port-Hamiltonian Architectural Bias for Long-Range Propagation in Deep Graph Networks
Simon Heilig, Alessio Gravina, Alessandro Trenta et al.
In-Context Editing: Learning Knowledge from Self-Induced Distributions
Siyuan Qi, Bangcheng Yang, Kailin Jiang et al.