Most Cited 2024 "encoder-decoder model" Papers

Fast Ensembling with Diffusion Schrödinger Bridge

Hyunsu Kim, Jongmin Yoon, Juho Lee

Benign Overfitting and Grokking in ReLU Networks for XOR Cluster Data

Zhiwei Xu, Yutong Wang, Spencer Frei et al.

L2P-MIP: Learning to Presolve for Mixed Integer Programming

Chang Liu, Zhichen Dong, Haobo Ma et al.

Neurosymbolic Grounding for Compositional World Models

Atharva Sehgal, Arya Grayeli, Jennifer Sun et al.

Momentum Benefits Non-iid Federated Learning Simply and Provably

Ziheng Cheng, Xinmeng Huang, Pengfei Wu et al.

Making Pre-trained Language Models Great on Tabular Prediction

Jiahuan Yan, Bo Zheng, Hongxia Xu et al.

Feature-aligned N-BEATS with Sinkhorn divergence

Joonhun Lee, Myeongho Jeon, Myungjoo Kang et al.

Exploiting Causal Graph Priors with Posterior Sampling for Reinforcement Learning

Mirco Mutti, Riccardo De Santi, Marcello Restelli et al.

Video Decomposition Prior: Editing Videos Layer by Layer

Gaurav Shrivastava, Ser-Nam Lim, Abhinav Shrivastava

New Insight of Variance reduce in Zero-Order Hard-Thresholding: Mitigating Gradient Error and Expansivity Contradictions

Xinzhe Yuan, William de Vazelhes, Bin Gu et al.

Subtractive Mixture Models via Squaring: Representation and Learning

Lorenzo Loconte, Aleksanteri Sladek, Stefan Mengel et al.

AutoDAN: Generating Stealthy Jailbreak Prompts on Aligned Large Language Models

Xiaogeng Liu, Nan Xu, Muhao Chen et al.

Bridging Vision and Language Spaces with Assignment Prediction

Jungin Park, Jiyoung Lee, Kwanghoon Sohn

Modulate Your Spectrum in Self-Supervised Learning

Xi Weng, Yunhao Ni, Tengwei Song et al.

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

Tomoya Murata, Kenta Niwa, Takumi Fukami et al.

Graph Parsing Networks

Yunchong Song, Siyuan Huang, Xinbing Wang et al.

Optimal transport based adversarial patch to leverage large scale attack transferability

Pol Labarbarie, Adrien CHAN-HON-TONG, Stéphane Herbin et al.

Orbit-Equivariant Graph Neural Networks

Matthew Morris, Bernardo Grau, Ian Horrocks

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

Aditya Chattopadhyay, Kwan Ho Ryan Chan, Rene Vidal

More is Better: when Infinite Overparameterization is Optimal and Overfitting is Obligatory

James Simon, Dhruva Karkada, Nikhil Ghosh et al.

An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression

Lijia Zhou, James Simon, Gal Vardi et al.

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

Zican Hu, Zongzhang Zhang, Huaxiong Li et al.

End-to-End (Instance)-Image Goal Navigation through Correspondence as an Emergent Phenomenon

Guillaume Bono, Leonid Antsfeld, Boris Chidlovskii et al.

Don't Judge by the Look: Towards Motion Coherent Video Representation

Yitian Zhang, Yue Bai, Huan Wang et al.

Submodular Reinforcement Learning

Manish Prajapat, Mojmir Mutny, Melanie Zeilinger 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.

A Versatile Causal Discovery Framework to Allow Causally-Related Hidden Variables

Xinshuai Dong, Biwei Huang, Ignavier Ng et al.

Inherently Interpretable Time Series Classification via Multiple Instance Learning

Joseph Early, Gavin Cheung, Kurt Cutajar et al.

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

Erik Schultheis, Wojciech Kotlowski, Marek Wydmuch et al.

KW-Design: Pushing the Limit of Protein Design via Knowledge Refinement

Zhangyang Gao, Cheng Tan, Xingran Chen et al.

MOTOR: A Time-to-Event Foundation Model For Structured Medical Records

Ethan Steinberg, Jason Fries, Yizhe Xu et al.

Constructing Adversarial Examples for Vertical Federated Learning: Optimal Client Corruption through Multi-Armed Bandit

Duanyi YAO, Songze Li, Ye XUE et al.

Learning with Mixture of Prototypes for Out-of-Distribution Detection

Haodong Lu, Dong Gong, Shuo Wang et al.

Efficient Continual Finite-Sum Minimization

Ioannis Mavrothalassitis, Stratis Skoulakis, Leello Dadi 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.

Magnitude Invariant Parametrizations Improve Hypernetwork Learning

Jose Javier Gonzalez Ortiz, John Guttag, Adrian Dalca

Building Cooperative Embodied Agents Modularly with Large Language Models

Hongxin Zhang, Weihua Du, Jiaming Shan et al.

Towards Robust Multi-Modal Reasoning via Model Selection

Xiangyan Liu, Rongxue LI, Wei Ji et al.

The optimality of kernel classifiers in Sobolev space

Jianfa Lai, zhifan Li, Dongming Huang et al.

Proving Test Set Contamination in Black-Box Language Models

Yonatan Oren, Nicole Meister, Niladri Chatterji et al.

SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression

Tim Dettmers, Ruslan Svirschevski, Vage Egiazarian et al.

Is ImageNet worth 1 video? Learning strong image encoders from 1 long unlabelled video

Shashank Venkataramanan, Mamshad Nayeem Rizve, Joao Carreira et al.

CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing

Zhibin Gou, Zhihong Shao, Yeyun Gong et al.

Learning model uncertainty as variance-minimizing instance weights

Nishant Jain, Karthikeyan Shanmugam, Pradeep Shenoy

A Hard-to-Beat Baseline for Training-free CLIP-based Adaptation

Zhengbo Wang, Jian Liang, Lijun Sheng et al.

Piecewise Linear Parametrization of Policies: Towards Interpretable Deep Reinforcement Learning

Maxime Wabartha, Joelle Pineau

PandaLM: An Automatic Evaluation Benchmark for LLM Instruction Tuning Optimization

Yidong Wang, Zhuohao Yu, Wenjin Yao et al.

Skill Machines: Temporal Logic Skill Composition in Reinforcement Learning

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

Designing Skill-Compatible AI: Methodologies and Frameworks in Chess

KARIM HAMADE, Reid McIlroy-Young, Siddhartha Sen et al.

Forward Learning with Top-Down Feedback: Empirical and Analytical Characterization

Ravi Srinivasan, Francesca Mignacco, Martino Sorbaro et al.

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

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

Mixture of LoRA Experts

xun wu, Shaohan Huang, Furu Wei

Knowledge Distillation Based on Transformed Teacher Matching

Kaixiang Zheng, EN-HUI YANG

Pseudo-Generalized Dynamic View Synthesis from a Video

Xiaoming Zhao, R Colburn, Fangchang Ma et al.

Learning Polynomial Problems with $SL(2, \mathbb{R})$-Equivariance

Hannah Lawrence, Mitchell Harris

Talk like a Graph: Encoding Graphs for Large Language Models

Bahare Fatemi, Jonathan Halcrow, Bryan Perozzi

Maximum Entropy Heterogeneous-Agent Reinforcement Learning

Jiarong Liu, Yifan Zhong, Siyi Hu et al.

Nougat: Neural Optical Understanding for Academic Documents

Lukas Blecher, Guillem Cucurull Preixens, Thomas Scialom et al.

Tree-Planner: Efficient Close-loop Task Planning with Large Language Models

Mengkang Hu, Yao Mu, Xinmiao Yu et al.

PINNsFormer: A Transformer-Based Framework For Physics-Informed Neural Networks

Zhiyuan Zhao, Xueying Ding, B. Aditya Prakash

NEFTune: Noisy Embeddings Improve Instruction Finetuning

Neel Jain, Ping-yeh Chiang, Yuxin Wen et al.

Entropy Coding of Unordered Data Structures

Julius Kunze, Daniel Severo, giulio zani et al.

A Semantic Invariant Robust Watermark for Large Language Models

Aiwei Liu, Leyi Pan, Xuming Hu et al.

Plug-and-Play Policy Planner for Large Language Model Powered Dialogue Agents

Yang Deng, Wenxuan Zhang, Wai Lam et al.

Long-tailed Diffusion Models with Oriented Calibration

Tianjiao Zhang, Huangjie Zheng, Jiangchao Yao et al.

QA-LoRA: Quantization-Aware Low-Rank Adaptation of Large Language Models

Yuhui Xu, Lingxi Xie, Xiaotao Gu et al.

Hybrid Internal Model: Learning Agile Legged Locomotion with Simulated Robot Response

Junfeng Long, ZiRui Wang, Quanyi Li et al.

Illusory Attacks: Information-theoretic detectability matters in adversarial attacks

Tim Franzmeyer, Stephen McAleer, Joao F. Henriques et al.

Differentiable Learning of Generalized Structured Matrices for Efficient Deep Neural Networks

Changwoo Lee, Hun-Seok Kim

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

Xinyu Yang, Victor Weixin Liang, James Y Zou

An Analytical Solution to Gauss-Newton Loss for Direct Image Alignment

Sergei Solonets, Daniil Sinitsyn, Lukas Von Stumberg et al.

De novo Protein Design Using Geometric Vector Field Networks

weian mao, Muzhi Zhu, Zheng Sun et al.

Sample-Efficient Quality-Diversity by Cooperative Coevolution

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

Weakly-supervised Audio Separation via Bi-modal Semantic Similarity

Tanvir Mahmud, Saeed Amizadeh, Kazuhito Koishida et al.

DecompOpt: Controllable and Decomposed Diffusion Models for Structure-based Molecular Optimization

Xiangxin Zhou, Xiwei Cheng, Yuwei Yang et al.

Toward Student-oriented Teacher Network Training for Knowledge Distillation

Chengyu Dong, Liyuan Liu, Jingbo Shang

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

Chencheng Cai, Xu Zhang, Edoardo Airoldi

Robust Adversarial Reinforcement Learning via Bounded Rationality Curricula

Aryaman Reddi, Maximilian Tölle, Jan Peters et al.

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

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

BioBridge: Bridging Biomedical Foundation Models via Knowledge Graphs

Zifeng Wang, Zichen Wang, Balasubramaniam Srinivasan et al.

Backdoor Secrets Unveiled: Identifying Backdoor Data with Optimized Scaled Prediction Consistency

Soumyadeep Pal, Yuguang Yao, Ren Wang et al.

DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models

Licheng Wen, DAOCHENG FU, Xin Li et al.

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

Hong Chen, Yipeng Zhang, Simin Wu et al.

Parsing neural dynamics with infinite recurrent switching linear dynamical systems

Victor Geadah, International Brain Laboratory, Jonathan Pillow

Chain of Hindsight aligns Language Models with Feedback

Hao Liu, Carmelo Sferrazza, Pieter Abbeel

Discovering Failure Modes of Text-guided Diffusion Models via Adversarial Search

Qihao Liu, Adam Kortylewski, Yutong Bai et al.

MAP IT to Visualize Representations

Robert Jenssen

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

Sheng Li, Chao Wu, Ao Li et al.

Revisiting Data Augmentation in Deep Reinforcement Learning

Jianshu Hu, Yunpeng Jiang, Paul Weng

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

Xingyao Wang, Zihan Wang, Jiateng Liu et al.

Doubly Robust Instance-Reweighted Adversarial Training

Daouda Sow, Sen Lin, Zhangyang Wang et al.

CRAFT: Customizing LLMs by Creating and Retrieving from Specialized Toolsets

Lifan Yuan, Yangyi Chen, Xingyao Wang et al.

Generative Judge for Evaluating Alignment

Junlong Li, Shichao Sun, Weizhe Yuan et al.

Demystifying Linear MDPs and Novel Dynamics Aggregation Framework

Joongkyu Lee, Min-hwan Oh

Language Modeling Is Compression

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

An Extensible Framework for Open Heterogeneous Collaborative Perception

Yifan Lu, Yue Hu, Yiqi Zhong et al.

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

Dustin Podell, Zion English, Kyle Lacey et al.

Accurate and Scalable Estimation of Epistemic Uncertainty for Graph Neural Networks

Puja Trivedi, Mark Heimann, Rushil Anirudh et al.

Replay across Experiments: A Natural Extension of Off-Policy RL

Dhruva Tirumala, Thomas Lampe, Jose Enrique Chen et al.

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

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

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

Anne Harrington, Vasha DuTell, Mark Hamilton et al.

Diverse Projection Ensembles for Distributional Reinforcement Learning

Moritz Akiya Zanger, Wendelin Boehmer, Matthijs T. J. Spaan

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

Jaehyeon Kim, Keon Lee, Seungjun Chung et al.

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

Qihan Ren, Jiayang Gao, Wen Shen et al.

Enhanced Face Recognition using Intra-class Incoherence Constraint

Yuanqing Huang, Yinggui Wang, Le Yang et al.

Global Optimality for Non-linear Constrained Restoration Problems via Invexity

Samuel Pinilla, Jeyan Thiyagalingam

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

Changyao Tian, Chenxin Tao, Jifeng Dai et al.

CrossQ: Batch Normalization in Deep Reinforcement Learning for Greater Sample Efficiency and Simplicity

Aditya Bhatt, Daniel Palenicek, Boris Belousov et al.

Mask-Based Modeling for Neural Radiance Fields

Ganlin Yang, Guoqiang Wei, Zhizheng Zhang et al.

MixSup: Mixed-grained Supervision for Label-efficient LiDAR-based 3D Object Detection

Yuxue Yang, Lue Fan, Zhaoxiang Zhang

Towards Understanding Sycophancy in Language Models

Mrinank Sharma, Meg Tong, Tomek Korbak et al.

Algorithms for Caching and MTS with reduced number of predictions

Karim Ahmed Abdel Sadek, Marek Elias

Learning to reconstruct signals from binary measurements alone

Laurent Jacques, Julián Tachella

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

Gianluca Scarpellini, Ksenia Konyushkova, Claudio Fantacci et al.

Towards Identifiable Unsupervised Domain Translation: A Diversified Distribution Matching Approach

Sagar Shrestha, Xiao Fu

Conditional Variational Diffusion Models

Gabriel della Maggiora, Luis A. Croquevielle, Nikita Deshpande et al.

Can LLM-Generated Misinformation Be Detected?

Canyu Chen, Kai Shu

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

Montgomery Bohde, Meng Liu, Alexandra Saxton et al.

Matrix Manifold Neural Networks++

Xuan Son Nguyen, Yang, Aymeric Histace

Neural Atoms: Propagating Long-range Interaction in Molecular Graphs through Efficient Communication Channel

Xuan Li, Zhanke Zhou, Jiangchao Yao et al.

Optimistic Bayesian Optimization with Unknown Constraints

Quoc Phong Nguyen, Wan Theng Ruth Chew, Le Song et al.

Less is More: One-shot Subgraph Reasoning on Large-scale Knowledge Graphs

Zhanke Zhou, Yongqi Zhang, Jiangchao Yao et al.

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

Murtaza Dalal, Tarun Chiruvolu, Devendra Chaplot et al.

Personalize Segment Anything Model with One Shot

Renrui Zhang, Zhengkai Jiang, Ziyu Guo et al.

On the generalization capacity of neural networks during generic multimodal reasoning

Takuya Ito, Soham Dan, Mattia Rigotti et al.

The Expressive Power of Low-Rank Adaptation

Yuchen Zeng, Kangwook Lee

Multi-Scale Representations by Varying Window Attention for Semantic Segmentation

Haotian Yan, Ming Wu, Chuang Zhang

Retrieval meets Long Context Large Language Models

Peng Xu, Wei Ping, Xianchao Wu et al.

Hiding in Plain Sight: Disguising Data Stealing Attacks in Federated Learning

Kostadin Garov, Dimitar I. Dimitrov, Nikola Jovanović et al.

A Branching Decoder for Set Generation

Zixian Huang, Gengyang Xiao, Yu Gu et al.

3D Feature Prediction for Masked-AutoEncoder-Based Point Cloud Pretraining

Siming Yan, Yuqi Yang, Yu-Xiao Guo et al.

A Graph is Worth 1-bit Spikes: When Graph Contrastive Learning Meets Spiking Neural Networks

Jintang Li, Huizhe Zhang, Ruofan Wu et al.

Deep Reinforcement Learning Guided Improvement Heuristic for Job Shop Scheduling

Cong Zhang, Zhiguang Cao, Wen Song et al.

Estimating Shape Distances on Neural Representations with Limited Samples

Dean Pospisil, Brett Larsen, Sarah Harvey et al.

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

Zhenting Wang, Chen Chen, Lingjuan Lyu et al.

Object centric architectures enable efficient causal representation learning

Amin Mansouri, Jason Hartford, Yan Zhang et al.

Pre-Training and Fine-Tuning Generative Flow Networks

Ling Pan, Moksh Jain, Kanika Madan et al.

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

Debiased Collaborative Filtering with Kernel-Based Causal Balancing

Haoxuan Li, Chunyuan Zheng, Yanghao Xiao et al.

Towards Non-Asymptotic Convergence for Diffusion-Based Generative Models

Gen Li, Yuting Wei, Yuxin Chen et al.

Reverse Forward Curriculum Learning for Extreme Sample and Demo Efficiency

Stone Tao, Arth Shukla, Tse-kai Chan et al.

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

LU YU, Avetik Karagulyan, Arnak Dalalyan

S$2$AC: Energy-Based Reinforcement Learning with Stein Soft Actor Critic

Safa Messaoud, Billel Mokeddem, Zhenghai Xue et al.

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

Ziyao Wang, Jianyu Wang, Ang Li

A Symmetry-Aware Exploration of Bayesian Neural Network Posteriors

Olivier Laurent, Emanuel Aldea, Gianni Franchi

SEA: Sparse Linear Attention with Estimated Attention Mask

Heejun Lee, Jina Kim, Jeff Willette et al.

Goodhart's Law in Reinforcement Learning

Jacek Karwowski, Oliver Hayman, Xingjian Bai et al.

ReFusion: Improving Natural Language Understanding with Computation-Efficient Retrieval Representation Fusion

Shangyu Wu, Ying Xiong, Yufei CUI et al.

An Emulator for Fine-tuning Large Language Models using Small Language Models

Eric Mitchell, Rafael Rafailov, Archit Sharma et al.

Neural Optimal Transport with General Cost Functionals

Arip Asadulaev, Alexander Korotin, Vage Egiazarian et al.

Bounding the Expected Robustness of Graph Neural Networks Subject to Node Feature Attacks

Yassine ABBAHADDOU, Sofiane ENNADIR, Johannes Lutzeyer et al.

COLLIE: Systematic Construction of Constrained Text Generation Tasks

Shunyu Yao, Howard Chen, Austin Hanjie et al.

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

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

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

Ling Yang, Zhilong Zhang, Zhaochen Yu et al.

VQGraph: Rethinking Graph Representation Space for Bridging GNNs and MLPs

Ling Yang, Ye Tian, Minkai Xu et al.

Expressive Losses for Verified Robustness via Convex Combinations

Alessandro De Palma, Rudy R Bunel, Krishnamurthy Dvijotham et al.

Language Model Cascades: Token-Level Uncertainty And Beyond

Neha Gupta, Harikrishna Narasimhan, Wittawat Jitkrittum 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.

Faithful Rule Extraction for Differentiable Rule Learning Models

Xiaxia Wang, David Jaime Tena Cucala, Bernardo Grau et al.

Quantifying Network Similarity using Graph Cumulants

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

Grokking as a First Order Phase Transition in Two Layer Networks

Noa Rubin, Inbar Seroussi, Zohar Ringel

Feature emergence via margin maximization: case studies in algebraic tasks

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

JointNet: Extending Text-to-Image Diffusion for Dense Distribution Modeling

Jingyang Zhang, Shiwei Li, Yuanxun Lu et al.

An operator preconditioning perspective on training in physics-informed machine learning

Tim De Ryck, Florent Bonnet, Siddhartha Mishra et al.

Confidential-DPproof: Confidential Proof of Differentially Private Training

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

Hindsight PRIORs for Reward Learning from Human Preferences

Mudit Verma, Katherine Metcalf

A Hierarchical Bayesian Model for Few-Shot Meta Learning

Minyoung Kim, Timothy Hospedales

The Alignment Problem from a Deep Learning Perspective

Richard Ngo, Lawrence Chan, Sören Mindermann

Neural Fine-Tuning Search for Few-Shot Learning

Panagiotis Eustratiadis, Łukasz Dudziak, Da Li et al.

FairTune: Optimizing Parameter Efficient Fine Tuning for Fairness in Medical Image Analysis

Raman Dutt, Ondrej Bohdal, Sotirios Tsaftaris et al.

Align With Purpose: Optimize Desired Properties in CTC Models with a General Plug-and-Play Framework

Eliya Segev, Maya Alroy, Ronen Katsir et al.

DIG In: Evaluating Disparities in Image Generations with Indicators for Geographic Diversity

Melissa Hall, Candace Ross, Adina Williams et al.

Memorization in Self-Supervised Learning Improves Downstream Generalization

Wenhao Wang, Muhammad Ahmad Kaleem, Adam Dziedzic et al.

Neural Active Learning Beyond Bandits

CARD: Channel Aligned Robust Blend Transformer for Time Series Forecasting

xue wang, Tian Zhou, Qingsong Wen et al.

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.

Explaining Time Series via Contrastive and Locally Sparse Perturbations

Zichuan Liu, Yingying ZHANG, Tianchun Wang et al.

Detecting Pretraining Data from Large Language Models

Weijia Shi, Anirudh Ajith, Mengzhou Xia et al.

A Fast and Provable Algorithm for Sparse Phase Retrieval

Jian-Feng Cai, Yu Long, Ruixue WEN et al.

Multilingual Jailbreak Challenges in Large Language Models

Yue Deng, Wenxuan Zhang, Sinno Pan et al.

Lemur: Harmonizing Natural Language and Code for Language Agents

Yiheng Xu, Hongjin SU, Chen Xing et al.

Window Attention is Bugged: How not to Interpolate Position Embeddings

Daniel Bolya, Chaitanya Ryali, Judy Hoffman et al.

Sharpness-Aware Data Poisoning Attack

Pengfei He, Han Xu, Jie Ren et al.

Faster Sampling from Log-Concave Densities over Polytopes via Efficient Linear Solvers

Oren Mangoubi, Nisheeth Vishnoi

Learning to Reject with a Fixed Predictor: Application to Decontextualization

Christopher Mohri, Daniel Andor, Eunsol Choi et al.

A 2-Dimensional State Space Layer for Spatial Inductive Bias

Ethan Baron, Itamar Zimerman, Lior Wolf

High-dimensional SGD aligns with emerging outlier eigenspaces

Gerard Ben Arous, Reza Gheissari, Jiaoyang Huang et al.

Dynamic Neural Response Tuning

Tian Qiu, Xu Wenxiang, lin chen et al.

Det-CGD: Compressed Gradient Descent with Matrix Stepsizes for Non-Convex Optimization

Hanmin Li, Avetik Karagulyan, Peter Richtarik

BatchPrompt: Accomplish more with less

Jianzhe Lin, Maurice Diesendruck, Liang Du et al.

CODE REPRESENTATION LEARNING AT SCALE

Dejiao Zhang, Wasi Ahmad, Ming Tan et al.

Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors

Guocheng Qian, Jinjie Mai, Abdullah Hamdi et al.

Forward Learning of Graph Neural Networks

Namyong Park, Xing Wang, Antoine Simoulin et al.

AutoChunk: Automated Activation Chunk for Memory-Efficient Deep Learning Inference

Xuanlei Zhao, Shenggan Cheng, Guangyang LU et al.

TorchRL: A data-driven decision-making library for PyTorch

Albert Bou, Matteo Bettini, Sebastian Dittert et al.

CellPLM: Pre-training of Cell Language Model Beyond Single Cells

Hongzhi Wen, Wenzhuo Tang, Xinnan Dai et al.