Most Cited 2024 Poster Papers
12,324 papers found • Page 41 of 62
Conference
Topological data analysis on noisy quantum computers
Ismail Akhalwaya, Shashanka Ubaru, Kenneth Clarkson et al.
VCR-Graphormer: A Mini-batch Graph Transformer via Virtual Connections
Dongqi Fu, Zhigang Hua, Yan Xie et al.
Soft Robust MDPs and Risk-Sensitive MDPs: Equivalence, Policy Gradient, and Sample Complexity
Runyu Zhang, Yang Hu, Na Li
Towards Non-Asymptotic Convergence for Diffusion-Based Generative Models
Gen Li, Yuting Wei, Yuxin Chen et al.
S$2$AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic
Safa Messaoud, Billel Mokeddem, Zhenghai Xue et al.
VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs
Ling Yang, Ye Tian, Minkai Xu et al.
A Linear Algebraic Framework for Counterfactual Generation
Jong-Hoon Ahn, Akshay Vashist
Learning to Reject Meets Long-tail Learning
Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum et al.
An operator preconditioning perspective on training in physics-informed machine learning
Tim De Ryck, Florent Bonnet, Siddhartha Mishra et al.
Hindsight PRIORs for Reward Learning from Human Preferences
Mudit Verma, Katherine Metcalf
The Alignment Problem from a Deep Learning Perspective
Richard Ngo, Lawrence Chan, Sören Mindermann
Pathformer: Multi-scale Transformers with Adaptive Pathways for Time Series Forecasting
Peng Chen, Yingying ZHANG, Yunyao Cheng et al.
EasyTPP: Towards Open Benchmarking Temporal Point Processes
Siqiao Xue, Xiaoming Shi, Zhixuan Chu et al.
Detecting Pretraining Data from Large Language Models
Weijia Shi, Anirudh Ajith, Mengzhou Xia et al.
BatchPrompt: Accomplish more with less
Jianzhe Lin, Maurice Diesendruck, Liang Du et al.
Forward Learning of Graph Neural Networks
Namyong Park, Xing Wang, Antoine Simoulin et al.
CellPLM: Pre-training of Cell Language Model Beyond Single Cells
Hongzhi Wen, Wenzhuo Tang, Xinnan Dai et al.
Meta-VBO: Utilizing Prior Tasks in Optimizing Risk Measures with Gaussian Processes
Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet
Temporal Generalization Estimation in Evolving Graphs
Bin Lu, Tingyan Ma, Xiaoying Gan et al.
Self-Alignment with Instruction Backtranslation
Xian Li, Ping Yu, Chunting Zhou et al.
Denoising Task Routing for Diffusion Models
Byeongjun Park, Sangmin Woo, Hyojun Go et al.
Likelihood Training of Cascaded Diffusion Models via Hierarchical Volume-preserving Maps
Henry Li, Ronen Basri, Yuval Kluger
TapMo: Shape-aware Motion Generation of Skeleton-free Characters
Jiaxu Zhang, Shaoli Huang, Zhigang Tu et al.
Tuning LayerNorm in Attention: Towards Efficient Multi-Modal LLM Finetuning
Bingchen Zhao, Haoqin Tu, Chen Wei et al.
Generalization in diffusion models arises from geometry-adaptive harmonic representations
Zahra Kadkhodaie, Florentin Guth, Eero Simoncelli et al.
Robust NAS under adversarial training: benchmark, theory, and beyond
Yongtao Wu, Fanghui Liu, Carl-Johann Simon-Gabriel et al.
Future Language Modeling from Temporal Document History
Changmao Li, Jeffrey Flanigan
SGD Finds then Tunes Features in Two-Layer Neural Networks with near-Optimal Sample Complexity: A Case Study in the XOR problem
Margalit Glasgow
ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference
Krzysztof Kacprzyk, Samuel Holt, Jeroen Berrevoets et al.
One-shot Empirical Privacy Estimation for Federated Learning
Galen Andrew, Peter Kairouz, Sewoong Oh et al.
Learning to Act from Actionless Videos through Dense Correspondences
Po-Chen Ko, Jiayuan Mao, Yilun Du et al.
The False Promise of Imitating Proprietary Language Models
Arnav Gudibande, Eric Wallace, Charlie Snell et al.
Offline RL with Observation Histories: Analyzing and Improving Sample Complexity
Joey Hong, Anca Dragan, Sergey Levine
Learning From Simplicial Data Based on Random Walks and 1D Convolutions
Florian Frantzen, Michael Schaub
Strategic Preys Make Acute Predators: Enhancing Camouflaged Object Detectors by Generating Camouflaged Objects
Chunming He, Kai Li, Yachao Zhang et al.
Revisiting the Last-Iterate Convergence of Stochastic Gradient Methods
Zijian Liu, Zhengyuan Zhou
Approximating Nash Equilibria in Normal-Form Games via Stochastic Optimization
Ian Gemp, Luke Marris, Georgios Piliouras
LLaMA-Adapter: Efficient Fine-tuning of Large Language Models with Zero-initialized Attention
Renrui Zhang, Jiaming Han, Chris Liu et al.
Exploring Diffusion Time-steps for Unsupervised Representation Learning
Zhongqi Yue, Zhongqi Yue, Jiankun Wang et al.
DiffAR: Denoising Diffusion Autoregressive Model for Raw Speech Waveform Generation
Roi Benita, Michael Elad, Joseph Keshet
Training Diffusion Models with Reinforcement Learning
Kevin Black, Michael Janner, Yilun Du et al.
Motif: Intrinsic Motivation from Artificial Intelligence Feedback
Martin Klissarov, Pierluca D'Oro, Shagun Sodhani et al.
Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation
Luca Eyring, Dominik Klein, Théo Uscidda et al.
Machine Unlearning for Image-to-Image Generative Models
Guihong Li, Hsiang Hsu, Chun-Fu Chen et al.
Emu: Generative Pretraining in Multimodality
Quan Sun, Qiying Yu, Yufeng Cui et al.
Candidate Label Set Pruning: A Data-centric Perspective for Deep Partial-label Learning
Shuo He, Chaojie Wang, Guowu Yang et al.
Quick-Tune: Quickly Learning Which Pretrained Model to Finetune and How
Sebastian Pineda Arango, Fabio Ferreira, Arlind Kadra et al.
Advancing Pose-Guided Image Synthesis with Progressive Conditional Diffusion Models
Fei Shen, Hu Ye, Jun Zhang et al.
The Generalization Gap in Offline Reinforcement Learning
Ishita Mediratta, Qingfei You, Minqi Jiang et al.
Principled Federated Domain Adaptation: Gradient Projection and Auto-Weighting
Enyi Jiang, Yibo Jacky Zhang, Sanmi Koyejo
TEST: Text Prototype Aligned Embedding to Activate LLM's Ability for Time Series
Chenxi Sun, Hongyan Li, Yaliang Li et al.
Teaching Large Language Models to Self-Debug
Xinyun Chen, Maxwell Lin, Nathanael Schaerli et al.
Take a Step Back: Evoking Reasoning via Abstraction in Large Language Models
Huaixiu Steven Zheng, Swaroop Mishra, Xinyun Chen et al.
Mixture-of-Experts Meets Instruction Tuning: A Winning Combination for Large Language Models
Sheng Shen, Le Hou, Yanqi Zhou et al.
CAS: A Probability-Based Approach for Universal Condition Alignment Score
Chunsan Hong, ByungHee Cha, Tae-Hyun Oh
Follow-Up Differential Descriptions: Language Models Resolve Ambiguities for Image Classification
Reza Esfandiarpoor, Stephen Bach
Idempotent Generative Network
Assaf Shocher, Amil Dravid, Yossi Gandelsman et al.
Achieving Fairness in Multi-Agent MDP Using Reinforcement Learning
Peizhong Ju, Arnob Ghosh, Ness Shroff
Tractable Probabilistic Graph Representation Learning with Graph-Induced Sum-Product Networks
Federico Errica, Mathias Niepert
Parameter-Efficient Multi-Task Model Fusion with Partial Linearization
Anke Tang, Li Shen, Yong Luo et al.
One For All: Towards Training One Graph Model For All Classification Tasks
Hao Liu, Jiarui Feng, Lecheng Kong et al.
$t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence
Juno Kim, Jaehyuk Kwon, Mincheol Cho et al.
Inverse Approximation Theory for Nonlinear Recurrent Neural Networks
Shida Wang, Zhong Li, Qianxiao Li
Understanding Addition in Transformers
Philip Quirke, Fazl Barez
PAE: Reinforcement Learning from External Knowledge for Efficient Exploration
Zhe Wu, Haofei Lu, Junliang Xing et al.
How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization
Nuoya Xiong, Lijun Ding, Simon Du
MT-Ranker: Reference-free machine translation evaluation by inter-system ranking
Ibraheem Muhammad Moosa, Rui Zhang, Wenpeng Yin
Parametric Augmentation for Time Series Contrastive Learning
Xu Zheng, Tianchun Wang, Wei Cheng et al.
On the Effect of Batch Size in Byzantine-Robust Distributed Learning
Yi-Rui Yang, Chang-Wei Shi, Wu-Jun Li
Harnessing Explanations: LLM-to-LM Interpreter for Enhanced Text-Attributed Graph Representation Learning
Xiaoxin He, Xavier Bresson, Thomas Laurent et al.
From Bricks to Bridges: Product of Invariances to Enhance Latent Space Communication
Irene Cannistraci, Luca Moschella, Marco Fumero et al.
Batched Low-Rank Adaptation of Foundation Models
Yeming Wen, Swarat Chaudhuri
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.
PromptAgent: Strategic Planning with Language Models Enables Expert-level Prompt Optimization
Xinyuan Wang, Chenxi Li, Zhen Wang et al.
Score-based generative models break the curse of dimensionality in learning a family of sub-Gaussian distributions
Frank Cole, Yulong Lu
Learning Performance-Improving Code Edits
Alexander Shypula, Aman Madaan, Yimeng Zeng et al.
Understanding Convergence and Generalization in Federated Learning through Feature Learning Theory
Wei Huang, Ye Shi, Zhongyi Cai et al.
MVSFormer++: Revealing the Devil in Transformer's Details for Multi-View Stereo
chenjie cao, xinlin ren, Yanwei Fu
DAFA: Distance-Aware Fair Adversarial Training
Hyungyu Lee, Saehyung Lee, Hyemi Jang et al.
Generating Pragmatic Examples to Train Neural Program Synthesizers
Saujas Vaduguru, Daniel Fried, Yewen Pu
Parameter-Efficient Orthogonal Finetuning via Butterfly Factorization
Weiyang Liu, Zeju Qiu, Yao Feng et al.
Learning with Language-Guided State Abstractions
Andi Peng, Ilia Sucholutsky, Belinda Li et al.
Successor Heads: Recurring, Interpretable Attention Heads In The Wild
Rhys Gould, Euan Ong, George Ogden et al.
On the Expressivity of Objective-Specification Formalisms in Reinforcement Learning
Rohan Subramani, Marcus Williams, Max Heitmann et al.
Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck
Marco Federici, Patrick Forré, Ryota Tomioka et al.
Enhancing Neural Subset Selection: Integrating Background Information into Set Representations
Binghui Xie, Yatao Bian, Kaiwen Zhou et al.
Partitioning Message Passing for Graph Fraud Detection
Wei Zhuo, Zemin Liu, Bryan Hooi et al.
Meta-Evolve: Continuous Robot Evolution for One-to-many Policy Transfer
Xingyu Liu, Deepak Pathak, DING ZHAO
Chain-of-Table: Evolving Tables in the Reasoning Chain for Table Understanding
Zilong Wang, Hao Zhang, Chun-Liang Li et al.
TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models
Zuxin Liu, Jesse Zhang, Kavosh Asadi et al.
Safe Collaborative Filtering
Riku Togashi, Tatsushi Oka, Naoto Ohsaka et al.
Analytically Tractable Hidden-States Inference in Bayesian Neural Networks
Luong-Ha Nguyen, James-A. Goulet
Automatic Functional Differentiation in JAX
Min Lin
$\mathcal{B}$-Coder: Value-Based Deep Reinforcement Learning for Program Synthesis
Zishun Yu, Yunzhe Tao, Liyu Chen et al.
Sample-efficient Learning of Infinite-horizon Average-reward MDPs with General Function Approximation
Jianliang He, Han Zhong, Zhuoran Yang
Fine-tuning Multimodal LLMs to Follow Zero-shot Demonstrative Instructions
Juncheng Li, Kaihang Pan, Zhiqi Ge et al.
Towards domain-invariant Self-Supervised Learning with Batch Styles Standardization
Marin Scalbert, Maria Vakalopoulou, Florent Couzinie-Devy
SNIP: Bridging Mathematical Symbolic and Numeric Realms with Unified Pre-training
Kazem Meidani, Parshin Shojaee, Chandan Reddy et al.
Transformer-Modulated Diffusion Models for Probabilistic Multivariate Time Series Forecasting
Yuxin Li, Wenchao Chen, Xinyue Hu et al.
Enhancing Small Medical Learners with Privacy-preserving Contextual Prompting
xinlu zhang, Shiyang Li, Xianjun Yang et al.
Intelligent Switching for Reset-Free RL
Darshan Patil, Janarthanan Rajendran, Glen Berseth et al.
Byzantine Robust Cooperative Multi-Agent Reinforcement Learning as a Bayesian Game
Simin Li, Jun Guo, Jingqiao Xiu et al.
#InsTag: Instruction Tagging for Analyzing Supervised Fine-tuning of Large Language Models
Keming Lu, Hongyi Yuan, Zheng Yuan et al.
Motion Guidance: Diffusion-Based Image Editing with Differentiable Motion Estimators
Daniel Geng, Andrew Owens
Exploring Target Representations for Masked Autoencoders
xingbin liu, Jinghao Zhou, Tao Kong et al.
Neural Language of Thought Models
Yi-Fu Wu, Minseung Lee, Sungjin Ahn
Statistical Rejection Sampling Improves Preference Optimization
Tianqi Liu, Yao Zhao, Rishabh Joshi et al.
Tell Your Model Where to Attend: Post-hoc Attention Steering for LLMs
Qingru Zhang, Chandan Singh, Liyuan Liu et al.
Privacy Amplification for Matrix Mechanisms
Christopher Choquette-Choo, Arun Ganesh, Thomas Steinke et al.
Constrained Bi-Level Optimization: Proximal Lagrangian Value Function Approach and Hessian-free Algorithm
Wei Yao, Chengming Yu, Shangzhi Zeng et al.
Geometry-Aware Projective Mapping for Unbounded Neural Radiance Fields
Junoh Lee, Hyunjun Jung, Jinhwi Park et al.
Identifiable Latent Polynomial Causal Models through the Lens of Change
Yuhang Liu, Zhen Zhang, Dong Gong et al.
Adaptive Regret for Bandits Made Possible: Two Queries Suffice
Zhou Lu, Qiuyi (Richard) Zhang, Xinyi Chen et al.
Thin-Shell Object Manipulations With Differentiable Physics Simulations
Yian Wang, Juntian Zheng, Zhehuan Chen et al.
Bayesian Coreset Optimization for Personalized Federated Learning
Prateek Chanda, Shrey Modi, Ganesh Ramakrishnan
Beyond Spatio-Temporal Representations: Evolving Fourier Transform for Temporal Graphs
Anson Simon Bastos, Kuldeep Singh, Abhishek Nadgeri et al.
Hierarchical Context Merging: Better Long Context Understanding for Pre-trained LLMs
Woomin Song, Seunghyuk Oh, Sangwoo Mo et al.
On the Over-Memorization During Natural, Robust and Catastrophic Overfitting
Runqi Lin, Chaojian Yu, Bo Han et al.
Mastering Memory Tasks with World Models
Mohammad Reza Samsami, Artem Zholus, Janarthanan Rajendran et al.
Towards Unified Multi-Modal Personalization: Large Vision-Language Models for Generative Recommendation and Beyond
Tianxin Wei, Bowen Jin, Ruirui Li et al.
DoLa: Decoding by Contrasting Layers Improves Factuality in Large Language Models
Yung-Sung Chuang, Yujia Xie, Hongyin Luo et al.
Augmenting Transformers with Recursively Composed Multi-grained Representations
Xiang Hu, Qingyang Zhu, Kewei Tu et al.
Learning Conditional Invariances through Non-Commutativity
Abhra Chaudhuri, Serban Georgescu, Anjan Dutta
Bandits Meet Mechanism Design to Combat Clickbait in Online Recommendation
Thomas Kleine Buening, Aadirupa Saha, Christos Dimitrakakis et al.
RobustTSF: Towards Theory and Design of Robust Time Series Forecasting with Anomalies
Hao Cheng, Qingsong Wen, Yang Liu et al.
ARGS: Alignment as Reward-Guided Search
Maxim Khanov, Jirayu Burapacheep, Yixuan Li
Let Models Speak Ciphers: Multiagent Debate through Embeddings
Chau Pham, Boyi Liu, Yingxiang Yang et al.
Understanding when Dynamics-Invariant Data Augmentations Benefit Model-free Reinforcement Learning Updates
Nicholas Corrado, Josiah Hanna
Text-to-3D with Classifier Score Distillation
Xin Yu, Yuan-Chen Guo, Yangguang Li et al.
Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning
HeeSun Bae, Seungjae Shin, Byeonghu Na et al.
Local Graph Clustering with Noisy Labels
Artur Back de Luca, Kimon Fountoulakis, Shenghao Yang
DistillSpec: Improving Speculative Decoding via Knowledge Distillation
Yongchao Zhou, Kaifeng Lyu, Ankit Singh Rawat et al.
Zero and Few-shot Semantic Parsing with Ambiguous Inputs
Elias Stengel-Eskin, Kyle Rawlins, Benjamin Van Durme
Large-Vocabulary 3D Diffusion Model with Transformer
Ziang Cao, Fangzhou Hong, Tong Wu et al.
Adversarial Attacks on Fairness of Graph Neural Networks
Binchi Zhang, Yushun Dong, Chen Chen et al.
Task structure and nonlinearity jointly determine learned representational geometry
Matteo Alleman, Jack Lindsey, Stefano Fusi
Graph Transformers on EHRs: Better Representation Improves Downstream Performance
Raphael Poulain, Rahmatollah Beheshti
SelfCheck: Using LLMs to Zero-Shot Check Their Own Step-by-Step Reasoning
Ning Miao, Yee Whye Teh, Tom Rainforth
Improved Regret Bounds for Non-Convex Online-Within-Online Meta Learning
Jiechao GUAN, Hui Xiong
Score Models for Offline Goal-Conditioned Reinforcement Learning
Harshit Sikchi, Rohan Chitnis, Ahmed Touati et al.
Learning Robust Generalizable Radiance Field with Visibility and Feature Augmented Point Representation
Jiaxu Wang, Ziyi Zhang, Renjing Xu
HoloNets: Spectral Convolutions do extend to Directed Graphs
Christian Koke, Daniel Cremers
Searching for High-Value Molecules Using Reinforcement Learning and Transformers
Raj Ghugare, Santiago Miret, Adriana Hugessen et al.
Interpretable Meta-Learning of Physical Systems
Matthieu Blanke, marc lelarge
Interpretable Sparse System Identification: Beyond Recent Deep Learning Techniques on Time-Series Prediction
Liu Xiaoyi, Duxin Chen, Wenjia Wei et al.
CircuitNet 2.0: An Advanced Dataset for Promoting Machine Learning Innovations in Realistic Chip Design Environment
Xun Jiang, zhuomin chai, Yuxiang Zhao et al.
Are Transformers with One Layer Self-Attention Using Low-Rank Weight Matrices Universal Approximators?
Tokio Kajitsuka, Issei Sato
Self-Supervised Contrastive Learning for Long-term Forecasting
Junwoo Park, Daehoon Gwak, Jaegul Choo et al.
Rethinking CNN’s Generalization to Backdoor Attack from Frequency Domain
Quanrui Rao, Lin Wang, Wuying Liu
Flow to Better: Offline Preference-based Reinforcement Learning via Preferred Trajectory Generation
Zhilong Zhang, Yihao Sun, Junyin Ye et al.
VBH-GNN: Variational Bayesian Heterogeneous Graph Neural Networks for Cross-subject Emotion Recognition
Chenyu Liu, XINLIANG ZHOU, Zhengri Zhu et al.
Harnessing Density Ratios for Online Reinforcement Learning
Philip Amortila, Dylan Foster, Nan Jiang et al.
Improved Efficiency Based on Learned Saccade and Continuous Scene Reconstruction From Foveated Visual Sampling
Jiayang Liu, Yiming Bu, Daniel Tso et al.
Local Composite Saddle Point Optimization
Site Bai, Brian Bullins
Improving Generalization of Alignment with Human Preferences through Group Invariant Learning
Rui Zheng, Wei Shen, Yuan Hua et al.
Improving LoRA in Privacy-preserving Federated Learning
Youbang Sun, Zitao Li, Yaliang Li et al.
Neural Neighborhood Search for Multi-agent Path Finding
Zhongxia Yan, Cathy Wu
How Does Unlabeled Data Provably Help Out-of-Distribution Detection?
Xuefeng Du, Zhen Fang, Ilias Diakonikolas et al.
GlucoBench: Curated List of Continuous Glucose Monitoring Datasets with Prediction Benchmarks
Renat Sergazinov, Elizabeth Chun, Valeriya Rogovchenko et al.
Look, Remember and Reason: Grounded Reasoning in Videos with Language Models
Apratim Bhattacharyya, Sunny Panchal, Reza Pourreza et al.
Pushing Boundaries: Mixup's Influence on Neural Collapse
Quinn Fisher, Haoming Meng, Vardan Papyan
LLCP: Learning Latent Causal Processes for Reasoning-based Video Question Answer
Guangyi Chen, Yuke Li, Xiao Liu et al.
Implicit regularization of deep residual networks towards neural ODEs
Pierre Marion, Yu-Han Wu, Michael Sander et al.
Compressing Latent Space via Least Volume
Qiuyi Chen, Mark Fuge
CoLiDE: Concomitant Linear DAG Estimation
Seyed Saman Saboksayr, Gonzalo Mateos, Mariano Tepper
Safe Offline Reinforcement Learning with Feasibility-Guided Diffusion Model
Yinan Zheng, Jianxiong Li, Dongjie Yu et al.
Spoken Question Answering and Speech Continuation Using Spectrogram-Powered LLM
Eliya Nachmani, Alon Levkovitch, Roy Hirsch et al.
Contrastive Preference Learning: Learning from Human Feedback without Reinforcement Learning
Joey Hejna, Rafael Rafailov, Harshit Sikchi et al.
Unknown Domain Inconsistency Minimization for Domain Generalization
Seungjae Shin, HeeSun Bae, Byeonghu Na et al.
Finite Scalar Quantization: VQ-VAE Made Simple
Fabian Mentzer, David Minnen, Eirikur Agustsson et al.
Fixed-Budget Differentially Private Best Arm Identification
Zhirui Chen, P. N. Karthik, Yeow Meng Chee et al.
FreeDyG: Frequency Enhanced Continuous-Time Dynamic Graph Model for Link Prediction
Yuxing Tian, Yiyan Qi, Fan Guo
Contrastive Learning is Spectral Clustering on Similarity Graph
Zhiquan Tan, Yifan Zhang, Jingqin Yang et al.
LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models
Gunho Park, baeseong park, Minsub Kim et al.
True Knowledge Comes from Practice: Aligning Large Language Models with Embodied Environments via Reinforcement Learning
Weihao Tan, Wentao Zhang, Shanqi Liu et al.
Dual Associated Encoder for Face Restoration
Yu-Ju Tsai, Yu-Lun Liu, Lu Qi et al.
Does Writing with Language Models Reduce Content Diversity?
Vishakh Padmakumar, He He
Few-shot Hybrid Domain Adaptation of Image Generator
Hengjia Li, Yang Liu, Linxuan Xia et al.
Adaptive Rational Activations to Boost Deep Reinforcement Learning
Quentin Delfosse, Patrick Schramowski, Martin Mundt et al.
Towards Meta-Pruning via Optimal Transport
Alexander Theus, Olin Geimer, Friedrich Wicke et al.
From Posterior Sampling to Meaningful Diversity in Image Restoration
Noa Cohen, Hila Manor, Yuval Bahat et al.
LMSYS-Chat-1M: A Large-Scale Real-World LLM Conversation Dataset
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng et al.
A Recipe for Improved Certifiable Robustness
Kai Hu, Klas Leino, Zifan Wang et al.
Uni-RLHF: Universal Platform and Benchmark Suite for Reinforcement Learning with Diverse Human Feedback
Yifu Yuan, Jianye HAO, Yi Ma et al.
Sample-Efficiency in Multi-Batch Reinforcement Learning: The Need for Dimension-Dependent Adaptivity
Emmeran Johnson, Ciara Pike-Burke, Patrick Rebeschini
Delphic Offline Reinforcement Learning under Nonidentifiable Hidden Confounding
Alizée Pace, Hugo Yèche, Bernhard Schoelkopf et al.
Label-free Node Classification on Graphs with Large Language Models (LLMs)
Zhikai Chen, Haitao Mao, Hongzhi Wen et al.
Function-space Parameterization of Neural Networks for Sequential Learning
Aidan Scannell, Riccardo Mereu, Paul Chang et al.
Boundary Denoising for Video Activity Localization
Mengmeng Xu, Mattia Soldan, Jialin Gao et al.
How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions
Lorenzo Pacchiardi, Alex Chan, Sören Mindermann et al.
Alt-Text with Context: Improving Accessibility for Images on Twitter
Nikita Srivatsan, Sofia Samaniego, Omar Florez et al.
Combinatorial Bandits for Maximum Value Reward Function under Value-Index Feedback
Yiliu Wang, Wei Chen, Milan Vojnovic
Yet Another ICU Benchmark: A Flexible Multi-Center Framework for Clinical ML
Robin van de Water, Hendrik Schmidt, Paul Elbers et al.
PixArt-$\alpha$: Fast Training of Diffusion Transformer for Photorealistic Text-to-Image Synthesis
Junsong Chen, Jincheng YU, Chongjian GE et al.
Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision
Nan Chen, Zemin Liu, Bryan Hooi et al.
Improving equilibrium propagation without weight symmetry through Jacobian homeostasis
Axel Laborieux, Friedemann Zenke
Object-Aware Inversion and Reassembly for Image Editing
Zhen Yang, Ganggui Ding, Wen Wang et al.
What's In My Big Data?
Yanai Elazar, Akshita Bhagia, Ian Magnusson et al.
Minimum width for universal approximation using ReLU networks on compact domain
Namjun Kim, Chanho Min, Sejun Park