Most Cited 2024 Poster Papers
12,324 papers found • Page 44 of 62
Conference
Scene Graph Generation Strategy with Co-occurrence Knowledge and Learnable Term Frequency
Hyeongjin Kim, Sangwon Kim, Dasom Ahn et al.
Towards General Algorithm Discovery for Combinatorial Optimization: Learning Symbolic Branching Policy from Bipartite Graph
Yufei Kuang, Jie Wang, Yuyan Zhou et al.
Flexible Residual Binarization for Image Super-Resolution
Yulun Zhang, Haotong Qin, Zixiang Zhao et al.
SFC: Achieve Accurate Fast Convolution under Low-precision Arithmetic
Liulu He, yufei zhao, rui gao et al.
Transformers, parallel computation, and logarithmic depth
Clayton Sanford, Daniel Hsu, Matus Telgarsky
Weakly-Supervised Residual Evidential Learning for Multi-Instance Uncertainty Estimation
Pei Liu, Luping Ji
Sliding Down the Stairs: How Correlated Latent Variables Accelerate Learning with Neural Networks
Lorenzo Bardone, Sebastian Goldt
Helpful or Harmful Data? Fine-tuning-free Shapley Attribution for Explaining Language Model Predictions
Jingtan Wang, Xiaoqiang Lin, Rui Qiao et al.
Rotational Equilibrium: How Weight Decay Balances Learning Across Neural Networks
Atli Kosson, Bettina Messmer, Martin Jaggi
Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics
Manuel Brenner, Florian Hess, Georgia Koppe et al.
When is Transfer Learning Possible?
My Phan, Kianté Brantley, Stephanie Milani et al.
Self-Consistency Training for Density-Functional-Theory Hamiltonian Prediction
He Zhang, Chang Liu, wang et al.
Generalization Analysis for Multi-Label Learning
Yi-Fan Zhang, Min-Ling Zhang
On the sample complexity of conditional independence testing with Von Mises estimator with application to causal discovery
Fateme Jamshidi, Luca Ganassali, Negar Kiyavash
Coarse-To-Fine Tensor Trains for Compact Visual Representations
Sebastian Loeschcke, Dan Wang, Christian Leth-Espensen et al.
How Smooth Is Attention?
Valérie Castin, Pierre Ablin, Gabriel Peyré
On the Nonlinearity of Layer Normalization
Yunhao Ni, Yuxin Guo, Junlong Jia et al.
Fundamental Limits of Distributed Covariance Matrix Estimation Under Communication Constraints
Mohammad Reza Rahmani, Mohammad Hossein Yassaee, Mohammad Ali Maddah Ali et al.
LoCoCo: Dropping In Convolutions for Long Context Compression
Ruisi Cai, Yuandong Tian, Zhangyang “Atlas” Wang et al.
MobileLLM: Optimizing Sub-billion Parameter Language Models for On-Device Use Cases
Zechun Liu, Changsheng Zhao, Forrest Iandola et al.
TravelPlanner: A Benchmark for Real-World Planning with Language Agents
Jian Xie, Kai Zhang, Jiangjie Chen et al.
Dense Reward for Free in Reinforcement Learning from Human Feedback
Alexander Chan, Hao Sun, Samuel Holt et al.
Training-Free Long-Context Scaling of Large Language Models
Chenxin An, Fei Huang, Jun Zhang et al.
MD tree: a model-diagnostic tree grown on loss landscape
Yefan Zhou, Jianlong Chen, Qinxue Cao et al.
Position: Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback
Vincent Conitzer, Rachel Freedman, Jobstq Heitzig et al.
PARDEN, Can You Repeat That? Defending against Jailbreaks via Repetition
Ziyang Zhang, Qizhen Zhang, Jakob Foerster
Craftax: A Lightning-Fast Benchmark for Open-Ended Reinforcement Learning
Michael Matthews, Michael Beukman, Benjamin Ellis et al.
Adaptive Online Experimental Design for Causal Discovery
Muhammad Qasim Elahi, Lai Wei, Murat Kocaoglu et al.
Joint Composite Latent Space Bayesian Optimization
Natalie Maus, Zhiyuan Jerry Lin, Maximilian Balandat et al.
Breaking the Barrier: Enhanced Utility and Robustness in Smoothed DRL Agents
Chung-En Sun, Sicun Gao, Lily Weng
Spectral Phase Transition and Optimal PCA in Block-Structured Spiked Models
Pierre Mergny, Justin Ko, FLORENT KRZAKALA
Uniform Memory Retrieval with Larger Capacity for Modern Hopfield Models
Dennis Wu, Jerry Yao-Chieh Hu, Teng-Yun Hsiao et al.
Agent Instructs Large Language Models to be General Zero-Shot Reasoners
Nicholas Crispino, Kyle Montgomery, Fankun Zeng et al.
Learning Linear Block Error Correction Codes
Yoni Choukroun, Lior Wolf
Private and Federated Stochastic Convex Optimization: Efficient Strategies for Centralized Systems
Roie Reshef, Kfir Levy
Dynamic Byzantine-Robust Learning: Adapting to Switching Byzantine Workers
Ron Dorfman, Naseem Yehya, Kfir Levy
Parameter-Dependent Competitive Analysis for Online Capacitated Coverage Maximization through Boostings and Attenuations
Pan Xu
Stochastic Q-learning for Large Discrete Action Spaces
Fares Fourati, Vaneet Aggarwal, Mohamed-Slim Alouini
Autoencoding Conditional Neural Processes for Representation Learning
Victor Prokhorov, Ivan Titov, Siddharth N
BLO-SAM: Bi-level Optimization Based Finetuning of the Segment Anything Model for Overfitting-Preventing Semantic Segmentation
Li Zhang, Youwei Liang, Ruiyi Zhang et al.
A Touch, Vision, and Language Dataset for Multimodal Alignment
Letian Fu, Gaurav Datta, Huang Huang et al.
On The Complexity of First-Order Methods in Stochastic Bilevel Optimization
Jeongyeol Kwon, Dohyun Kwon, Hanbaek Lyu
Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning
Sungmin Cha, Kyunghyun Cho, Taesup Moon
Block Acceleration Without Momentum: On Optimal Stepsizes of Block Gradient Descent for Least-Squares
Liangzu Peng, Wotao Yin
Improving Group Robustness on Spurious Correlation Requires Preciser Group Inference
Yujin Han, Difan Zou
Self-cognitive Denoising in the Presence of Multiple Noisy Label Sources
Yi-Xuan Sun, Ya-Lin Zhang, BIN HAN et al.
Explaining Graph Neural Networks via Structure-aware Interaction Index
Ngoc Bui, Trung Hieu Nguyen, Viet Anh Nguyen et al.
Generative Conditional Distributions by Neural (Entropic) Optimal Transport
Bao Nguyen, Binh Nguyen, Trung Hieu Nguyen et al.
Federated Continual Learning via Prompt-based Dual Knowledge Transfer
Hongming Piao, Yichen WU, Dapeng Wu et al.
xT: Nested Tokenization for Larger Context in Large Images
Ritwik Gupta, Shufan Li, Tyler Zhu et al.
SAM-E: Leveraging Visual Foundation Model with Sequence Imitation for Embodied Manipulation
Junjie Zhang, Chenjia Bai, Haoran He et al.
Toward Adaptive Reasoning in Large Language Models with Thought Rollback
Sijia Chen, Baochun Li
Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs
Langzhang Liang, Sunwoo Kim, Kijung Shin et al.
Privacy Profiles for Private Selection
Antti Koskela, Rachel Redberg, Yu-Xiang Wang
Improving Neural Logic Machines via Failure Reflection
Zhiming Li, Yushi Cao, Yan Zheng et al.
Less is More: on the Over-Globalizing Problem in Graph Transformers
Yujie Xing, Xiao Wang, Yibo Li et al.
Quantum Algorithms and Lower Bounds for Finite-Sum Optimization
Yexin Zhang, Chenyi Zhang, Cong Fang et al.
Stochastic Localization via Iterative Posterior Sampling
Louis Grenioux, Maxence Noble, Marylou Gabrié et al.
Learning Modality Knowledge Alignment for Cross-Modality Transfer
Wenxuan Ma, Shuang Li, Lincan Cai et al.
A Nearly Optimal Single Loop Algorithm for Stochastic Bilevel Optimization under Unbounded Smoothness
Xiaochuan Gong, Jie Hao, Mingrui Liu
Energy-Efficient Gaussian Processes Using Low-Precision Arithmetic
Nicolas Alder, Ralf Herbrich
LoRA Training in the NTK Regime has No Spurious Local Minima
Uijeong Jang, Jason Lee, Ernest Ryu
Mol-AE: Auto-Encoder Based Molecular Representation Learning With 3D Cloze Test Objective
Junwei Yang, Kangjie Zheng, Siyu Long et al.
ESM All-Atom: Multi-Scale Protein Language Model for Unified Molecular Modeling
Kangjie Zheng, Siyu Long, Tianyu Lu et al.
Pruned Pivot: Correlation Clustering Algorithm for Dynamic, Parallel, and Local Computation Models
Mina Dalirrooyfard, Konstantin Makarychev, Slobodan Mitrovic
MH-pFLID: Model Heterogeneous personalized Federated Learning via Injection and Distillation for Medical Data Analysis
Luyuan Xie, Manqing Lin, Tianyu Luan et al.
Discovering Multiple Solutions from a Single Task in Offline Reinforcement Learning
Takayuki Osa, Tatsuya Harada
Towards Resource-friendly, Extensible and Stable Incomplete Multi-view Clustering
Shengju Yu, Dong Zhibin, Siwei Wang et al.
Confidence Aware Inverse Constrained Reinforcement Learning
Sriram Ganapathi Subramanian, Guiliang Liu, Mohammed Elmahgiubi et al.
Solving Poisson Equations using Neural Walk-on-Spheres
Hong Chul Nam, Julius Berner, Anima Anandkumar
Flextron: Many-in-One Flexible Large Language Model
Ruisi Cai, Saurav Muralidharan, Greg Heinrich et al.
MLLM-as-a-Judge: Assessing Multimodal LLM-as-a-Judge with Vision-Language Benchmark
Dongping Chen, Ruoxi Chen, Shilin Zhang et al.
Prior Mismatch and Adaptation in PnP-ADMM with a Nonconvex Convergence Analysis
Shirin Shoushtari, JIAMING LIU, Edward Chandler et al.
DecisionNCE: Embodied Multimodal Representations via Implicit Preference Learning
Jianxiong Li, Jinliang Zheng, Yinan Zheng et al.
Learning to Compile Programs to Neural Networks
Logan Weber, Jesse Michel, Alex Renda et al.
FedLMT: Tackling System Heterogeneity of Federated Learning via Low-Rank Model Training with Theoretical Guarantees
Jiahao Liu, Yipeng Zhou, Di Wu et al.
ELF: Encoding Speaker-Specific Latent Speech Feature for Speech Synthesis
Jungil Kong, Junmo Lee, Jeongmin Kim et al.
Towards the Theory of Unsupervised Federated Learning: Non-asymptotic Analysis of Federated EM Algorithms
Ye Tian, Haolei Weng, Yang Feng
Bridging Environments and Language with Rendering Functions and Vision-Language Models
Théo Cachet, Christopher Dance, Olivier Sigaud
MoMo: Momentum Models for Adaptive Learning Rates
Fabian Schaipp, Ruben Ohana, Michael Eickenberg et al.
Multi-Fidelity Residual Neural Processes for Scalable Surrogate Modeling
Brooks(Ruijia) Niu, Dongxia Wu, Kai Kim et al.
Prompting4Debugging: Red-Teaming Text-to-Image Diffusion Models by Finding Problematic Prompts
Zhi-Yi Chin, Chieh Ming Jiang, Ching-Chun Huang et al.
Gambling-Based Confidence Sequences for Bounded Random Vectors
Jongha (Jon) Ryu, Gregory Wornell
Mitigating Oversmoothing Through Reverse Process of GNNs for Heterophilic Graphs
MoonJeong Park, Jaeseung Heo, Dongwoo Kim
From Self-Attention to Markov Models: Unveiling the Dynamics of Generative Transformers
Muhammed Emrullah Ildiz, Yixiao HUANG, Yingcong Li et al.
Online Linear Regression in Dynamic Environments via Discounting
Andrew Jacobsen, Ashok Cutkosky
Uncertainty for Active Learning on Graphs
Dominik Fuchsgruber, Tom Wollschläger, Bertrand Charpentier et al.
The Benefits of Reusing Batches for Gradient Descent in Two-Layer Networks: Breaking the Curse of Information and Leap Exponents
Yatin Dandi, Emanuele Troiani, Luca Arnaboldi et al.
Towards Realistic Model Selection for Semi-supervised Learning
Muyang Li, Xiaobo Xia, Runze Wu et al.
Finite Time Logarithmic Regret Bounds for Self-Tuning Regulation
Rahul Singh, Akshay Mete, Avik Kar et al.
On the Unexpected Effectiveness of Reinforcement Learning for Sequential Recommendation
Álvaro Labarca Silva, Denis Parra, Rodrigo A Toro Icarte
On Online Experimentation without Device Identifiers
Shiv Shankar, Ritwik Sinha, Madalina Fiterau
HarmBench: A Standardized Evaluation Framework for Automated Red Teaming and Robust Refusal
Mantas Mazeika, Long Phan, Xuwang Yin et al.
Do Efficient Transformers Really Save Computation?
Kai Yang, Jan Ackermann, Zhenyu He et al.
Sequence Compression Speeds Up Credit Assignment in Reinforcement Learning
Aditya A. Ramesh, Kenny Young, Louis Kirsch et al.
GPTSwarm: Language Agents as Optimizable Graphs
Mingchen Zhuge, Wenyi Wang, Louis Kirsch et al.
Provably Robust DPO: Aligning Language Models with Noisy Feedback
Sayak Ray Chowdhury, Anush Kini, Nagarajan Natarajan
Path-Guided Particle-based Sampling
Mingzhou Fan, Ruida Zhou, Chao Tian et al.
An Information-Theoretic Analysis of In-Context Learning
Hong Jun Jeon, Jason Lee, Qi Lei et al.
Balancing Feature Similarity and Label Variability for Optimal Size-Aware One-shot Subset Selection
Abhinab Acharya, Dayou Yu, Qi Yu et al.
A New Robust Partial p-Wasserstein-Based Metric for Comparing Distributions
Sharath Raghvendra, Pouyan Shirzadian, Kaiyi Zhang
Fast Timing-Conditioned Latent Audio Diffusion
Zach Evans, CJ Carr, Josiah Taylor et al.
Density-Softmax: Efficient Test-time Model for Uncertainty Estimation and Robustness under Distribution Shifts
Ha Manh Bui, Anqi Liu
Allocation Requires Prediction Only if Inequality Is Low
Ali Shirali, Rediet Abebe, Moritz Hardt
Can Gaussian Sketching Converge Faster on a Preconditioned Landscape?
Yilong Wang, Haishan Ye, Guang Dai et al.
Bespoke Non-Stationary Solvers for Fast Sampling of Diffusion and Flow Models
Neta Shaul, Uriel Singer, Ricky T. Q. Chen et al.
Variational Schrödinger Diffusion Models
Wei Deng, Weijian Luo, Yixin Tan et al.
Improving Transformers with Dynamically Composable Multi-Head Attention
Da Xiao, Qingye Meng, Shengping Li et al.
Constrained Exploration via Reflected Replica Exchange Stochastic Gradient Langevin Dynamics
Haoyang Zheng, Hengrong Du, Qi Feng et al.
Learning Universal Predictors
Jordi Grau-Moya, Tim Genewein, Marcus Hutter et al.
Memoria: Resolving Fateful Forgetting Problem through Human-Inspired Memory Architecture
Sangjun Park, JinYeong Bak
Surprisingly Strong Performance Prediction with Neural Graph Features
Gabriela Kadlecová, Jovita Lukasik, Martin Pilát et al.
GiLOT: Interpreting Generative Language Models via Optimal Transport
Xuhong Li, Jiamin Chen, Yekun Chai et al.
Prompt Sketching for Large Language Models
Luca Beurer-Kellner, Mark Müller, Marc Fischer et al.
Diversified Batch Selection for Training Acceleration
Feng Hong, Yueming LYU, Jiangchao Yao et al.
Rethinking Data Shapley for Data Selection Tasks: Misleads and Merits
Jiachen Wang, Tianji Yang, James Zou et al.
Scaling Laws for the Value of Individual Data Points in Machine Learning
Ian Covert, Wenlong Ji, Tatsunori Hashimoto et al.
In-context Vectors: Making In Context Learning More Effective and Controllable Through Latent Space Steering
Sheng Liu, Haotian Ye, Lei Xing et al.
Prospector Heads: Generalized Feature Attribution for Large Models & Data
Gautam Machiraju, Alexander Derry, Arjun Desai et al.
Audio Flamingo: A Novel Audio Language Model with Few-Shot Learning and Dialogue Abilities
Zhifeng Kong, ARUSHI GOEL, Rohan Badlani et al.
An Explicit Frame Construction for Normalizing 3D Point Clouds
Justin Baker, Shih-Hsin Wang, Tommaso de Fernex et al.
Distributional Bellman Operators over Mean Embeddings
Li Kevin Wenliang, Gregoire Deletang, Matthew Aitchison et al.
Comparing Graph Transformers via Positional Encodings
Mitchell Black, Zhengchao Wan, Gal Mishne et al.
ETHER: Efficient Finetuning of Large-Scale Models with Hyperplane Reflections
Massimo Bini, Karsten Roth, Zeynep Akata et al.
DéjàVu: KV-cache Streaming for Fast, Fault-tolerant Generative LLM Serving
Foteini Strati, Sara McAllister, Amar Phanishayee et al.
Private Heterogeneous Federated Learning Without a Trusted Server Revisited: Error-Optimal and Communication-Efficient Algorithms for Convex Losses
Changyu Gao, Andrew Lowy, Xingyu Zhou et al.
Incremental Topological Ordering and Cycle Detection with Predictions
Samuel McCauley, Benjamin Moseley, Aidin Niaparast et al.
A Linear Time and Space Local Point Cloud Geometry Encoder via Vectorized Kernel Mixture (VecKM)
Dehao Yuan, Cornelia Fermuller, Tahseen Rabbani et al.
How Deep Do We Need: Accelerating Training and Inference of Neural ODEs via Control Perspective
Keyan Miao, Konstantinos Gatsis
GPT-4V(ision) is a Generalist Web Agent, if Grounded
Boyuan Zheng, Boyu Gou, Jihyung Kil et al.
Scalable and Flexible Causal Discovery with an Efficient Test for Adjacency
Alan Amin, Andrew Wilson
NExT-Chat: An LMM for Chat, Detection and Segmentation
Ao Zhang, Yuan Yao, Wei Ji et al.
CKGConv: General Graph Convolution with Continuous Kernels
Liheng Ma, Soumyasundar Pal, Yitian Zhang et al.
${\rm E}(3)$-Equivariant Actor-Critic Methods for Cooperative Multi-Agent Reinforcement Learning
Dingyang Chen, Qi Zhang
Monitoring AI-Modified Content at Scale: A Case Study on the Impact of ChatGPT on AI Conference Peer Reviews
Weixin Liang, Zachary Izzo, Yaohui Zhang et al.
Cell2Sentence: Teaching Large Language Models the Language of Biology
Daniel Levine, Syed Rizvi, Sacha Lévy et al.
The Effect of Weight Precision on the Neuron Count in Deep ReLU Networks
Songhua He, Periklis Papakonstantinou
Perturb-and-Project: Differentially Private Similarities and Marginals
Vincent Cohen-Addad, Tommaso d'Orsi, Alessandro Epasto et al.
A Field Guide for Pacing Budget and ROS Constraints
Santiago Balseiro, Kshipra Bhawalkar, Zhe Feng et al.
PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control
Ruijie Zheng, Ching-An Cheng, Hal Daumé et al.
Deep Networks Always Grok and Here is Why
Ahmed Imtiaz Humayun, Randall Balestriero, Richard Baraniuk
Iterative Preference Learning from Human Feedback: Bridging Theory and Practice for RLHF under KL-constraint
Wei Xiong, Hanze Dong, Chenlu Ye et al.
Learning Decision Trees and Forests with Algorithmic Recourse
Kentaro Kanamori, Takuya Takagi, Ken Kobayashi et al.
Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients
Mengmeng Ma, Tang Li, Xi Peng
Differentiable Distributionally Robust Optimization Layers
Xutao Ma, Chao Ning, WenLi Du
TimeX++: Learning Time-Series Explanations with Information Bottleneck
Zichuan Liu, Tianchun Wang, Jimeng Shi et al.
NaturalSpeech 3: Zero-Shot Speech Synthesis with Factorized Codec and Diffusion Models
Zeqian Ju, Yuancheng Wang, Kai Shen et al.
Is DPO Superior to PPO for LLM Alignment? A Comprehensive Study
Shusheng Xu, Wei Fu, Jiaxuan Gao et al.
Open-Domain Text Evaluation via Contrastive Distribution Methods
Sidi Lu, Hongyi Liu, Asli Celikyilmaz et al.
DiNADO: Norm-Disentangled Neurally-Decomposed Oracles for Controlling Language Models
Sidi Lu, Wenbo Zhao, Chenyang Tao et al.
GATE: How to Keep Out Intrusive Neighbors
Nimrah Mustafa, Rebekka Burkholz
End-to-End Neuro-Symbolic Reinforcement Learning with Textual Explanations
Lirui Luo, Guoxi Zhang, Hongming Xu et al.
Position: Data-driven Discovery with Large Generative Models
Bodhisattwa Prasad Majumder, Harshit Surana, Dhruv Agarwal et al.
Information Flow in Self-Supervised Learning
Zhiquan Tan, Jingqin Yang, Weiran Huang et al.
Better & Faster Large Language Models via Multi-token Prediction
Fabian Gloeckle, Badr Youbi Idrissi, Baptiste Roziere et al.
CosPGD: an efficient white-box adversarial attack for pixel-wise prediction tasks
Shashank Agnihotri, Steffen Jung, Margret Keuper
Debating with More Persuasive LLMs Leads to More Truthful Answers
Akbir Khan, John Hughes, Dan Valentine et al.
Genie: Generative Interactive Environments
Jake Bruce, Michael Dennis, Ashley Edwards et al.
ATraDiff: Accelerating Online Reinforcement Learning with Imaginary Trajectories
Qianlan Yang, Yu-Xiong Wang
Data-Efficient Molecular Generation with Hierarchical Textual Inversion
Seojin Kim, Jaehyun Nam, Sihyun Yu et al.
All-in-one simulation-based inference
Manuel Gloeckler, Michael Deistler, Christian Weilbach et al.
Position: A Safe Harbor for AI Evaluation and Red Teaming
Shayne Longpre, Sayash Kapoor, Kevin Klyman et al.
Position: Future Directions in the Theory of Graph Machine Learning
Christopher Morris, Fabrizio Frasca, Nadav Dym et al.
Hierarchical Integral Probability Metrics: A distance on random probability measures with low sample complexity
Marta Catalano, Hugo Lavenant
HexGen: Generative Inference of Large Language Model over Heterogeneous Environment
Youhe Jiang, Ran Yan, Xiaozhe Yao et al.
Position: An Inner Interpretability Framework for AI Inspired by Lessons from Cognitive Neuroscience
Martina G. Vilas, Federico Adolfi, David Poeppel et al.
Implicit Bias of Policy Gradient in Linear Quadratic Control: Extrapolation to Unseen Initial States
Noam Razin, Yotam Alexander, Edo Cohen-Karlik et al.
Differentially Private Representation Learning via Image Captioning
Tom Sander, Yaodong Yu, Maziar Sanjabi et al.
PlanDQ: Hierarchical Plan Orchestration via D-Conductor and Q-Performer
Chang Chen, Junyeob Baek, Fei Deng et al.
On Gradient-like Explanation under a Black-box Setting: When Black-box Explanations Become as Good as White-box
Yi Cai, Gerhard Wunder
Neural operators meet conjugate gradients: The FCG-NO method for efficient PDE solving
Alexander Rudikov, Fanaskov Vladimir, Ekaterina Muravleva et al.
No Double Descent in Principal Component Regression: A High-Dimensional Analysis
Daniel Gedon, Antonio Ribeiro, Thomas Schön
Rethinking the Flat Minima Searching in Federated Learning
Taehwan Lee, Sung Whan Yoon
AutoOS: Make Your OS More Powerful by Exploiting Large Language Models
Huilai Chen, Yuanbo Wen, Limin Cheng et al.
Gradient-based Visual Explanation for Transformer-based CLIP
Chenyang ZHAO, Kun Wang, Xingyu Zeng et al.
Performance Bounds for Active Binary Testing with Information Maximization
Aditya Chattopadhyay, Benjamin Haeffele, Rene Vidal et al.
AegisFL: Efficient and Flexible Privacy-Preserving Byzantine-Robust Cross-silo Federated Learning
Dong Chen, Hongyuan Qu, Guangwu Xu
One for All: A Universal Generator for Concept Unlearnability via Multi-Modal Alignment
Chaochao Chen, Jiaming Zhang, Yuyuan Li et al.
Forget Sharpness: Perturbed Forgetting of Model Biases Within SAM Dynamics
Ankit Vani, Frederick Tung, Gabriel Oliveira et al.
Just Cluster It: An Approach for Exploration in High-Dimensions using Clustering and Pre-Trained Representations
Stefan Sylvius Wagner Martinez, Stefan Harmeling
Risk Aware Benchmarking of Large Language Models
Apoorva Nitsure, Youssef Mroueh, Mattia Rigotti et al.
To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning in Large Language Models
George-Octavian Bărbulescu, Peter Triantafillou
S$\Omega$I: Score-based O-INFORMATION Estimation
Mustapha BOUNOUA, Giulio Franzese, Pietro Michiardi
DeepPolar: Inventing Nonlinear Large-Kernel Polar Codes via Deep Learning
Ashwin Hebbar, Sravan Kumar Ankireddy, Hyeji Kim et al.
Position: On the Possibilities of AI-Generated Text Detection
Souradip Chakraborty, Amrit Singh Bedi, Sicheng Zhu et al.
MaxMin-RLHF: Alignment with Diverse Human Preferences
Souradip Chakraborty, Jiahao Qiu, Hui Yuan et al.
Don't be so Negative! Score-based Generative Modeling with Oracle-assisted Guidance
Saeid Naderiparizi, Xiaoxuan Liang, Setareh Cohan et al.
Quantum Theory and Application of Contextual Optimal Transport
Nicola Mariella, Albert Akhriev, Francesco Tacchino et al.
Learning with Partial-Label and Unlabeled Data: A Uniform Treatment for Supervision Redundancy and Insufficiency
Yangfan Liu, JIAQI LYU, Xin Geng et al.
AlphaZero-Like Tree-Search can Guide Large Language Model Decoding and Training
Ziyu Wan, Xidong Feng, Muning Wen et al.
Disentanglement Learning via Topology
Nikita Balabin, Daria Voronkova, Ilya Trofimov et al.
Quality-Diversity Actor-Critic: Learning High-Performing and Diverse Behaviors via Value and Successor Features Critics
Luca Grillotti, Maxence Faldor, Borja G. León et al.
Position: Embracing Negative Results in Machine Learning
Florian Karl, Malte Kemeter, Gabriel Dax et al.
Position: Reinforcement Learning in Dynamic Treatment Regimes Needs Critical Reexamination
Zhiyao Luo, Yangchen Pan, Peter Watkinson et al.
Learning Divergence Fields for Shift-Robust Graph Representations
Qitian Wu, Fan Nie, Chenxiao Yang et al.
Stay on Topic with Classifier-Free Guidance
Guillaume Sanchez, Alexander Spangher, Honglu Fan et al.
Position: On the Societal Impact of Open Foundation Models
Sayash Kapoor, Rishi Bommasani, Kevin Klyman et al.
Learning Label Shift Correction for Test-Agnostic Long-Tailed Recognition
Tong Wei, Zhen Mao, Zi-Hao Zhou et al.
On the Recoverability of Causal Relations from Temporally Aggregated I.I.D. Data
Shunxing Fan, Mingming Gong, Kun Zhang
Evaluation of Test-Time Adaptation Under Computational Time Constraints
Motasem Alfarra, Hani Itani, Alejandro Pardo et al.