Most Cited 2024 "interpretable prediction networks" Papers

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.

MetaPhysiCa: Improving OOD Robustness in Physics-informed Machine Learning

S Chandra Mouli, Muhammad Alam, Bruno Ribeiro

Counting Graph Substructures with Graph Neural Networks

Charilaos Kanatsoulis, Alejandro Ribeiro

Meta-VBO: Utilizing Prior Tasks in Optimizing Risk Measures with Gaussian Processes

Quoc Phong Nguyen, Bryan Kian Hsiang Low, Patrick Jaillet

Beyond Accuracy: Evaluating Self-Consistency of Code Large Language Models with IdentityChain

Marcus J. Min, Yangruibo Ding, Luca Buratti et al.

Beyond Imitation: Leveraging Fine-grained Quality Signals for Alignment

Geyang Guo, Ranchi Zhao, Tianyi Tang et al.

In-Context Learning through the Bayesian Prism

Madhur Panwar, Kabir Ahuja, Navin Goyal

Improving Domain Generalization with Domain Relations

Huaxiu Yao, Xinyu Yang, Xinyi Pan et al.

Analyzing and Mitigating Object Hallucination in Large Vision-Language Models

Yiyang Zhou, Chenhang Cui, Jaehong Yoon et al.

Zoology: Measuring and Improving Recall in Efficient Language Models

Simran Arora, Sabri Eyuboglu, Aman Timalsina et al.

Protein-Ligand Interaction Prior for Binding-aware 3D Molecule Diffusion Models

Zhilin Huang, Ling Yang, Xiangxin Zhou et al.

TRAM: Bridging Trust Regions and Sharpness Aware Minimization

Tom Sherborne, Naomi Saphra, Pradeep Dasigi et al.

Holistic Evaluation of Language Models

Jue Wang, Lucia Zheng, Nathan Kim et al.

Temporal Generalization Estimation in Evolving Graphs

Bin Lu, Tingyan Ma, Xiaoying Gan et al.

DynaVol: Unsupervised Learning for Dynamic Scenes through Object-Centric Voxelization

Yanpeng Zhao, Siyu Gao, Yunbo Wang 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

"What Data Benefits My Classifier?" Enhancing Model Performance and Interpretability through Influence-Based Data Selection

Anshuman Chhabra, Peizhao Li, Prasant Mohapatra et al.

TapMo: Shape-aware Motion Generation of Skeleton-free Characters

Jiaxu Zhang, Shaoli Huang, Zhigang Tu et al.

Pose Modulated Avatars from Video

Chunjin Song, Bastian Wandt, Helge Rhodin

MovingParts: Motion-based 3D Part Discovery in Dynamic Radiance Field

Kaizhi Yang, Xiaoshuai Zhang, Zhiao Huang et al.

CausalTime: Realistically Generated Time-series for Benchmarking of Causal Discovery

YUXIAO CHENG, Ziqian Wang, Tingxiong Xiao et al.

Near-Optimal Quantum Algorithm for Minimizing the Maximal Loss

Hao Wang, Chenyi Zhang, Tongyang Li

Contextual Bandits with Online Neural Regression

Rohan Deb, Yikun Ban, Shiliang Zuo et al.

Predictive auxiliary objectives in deep RL mimic learning in the brain

Ching Fang, Kimberly Stachenfeld

Mathematical Justification of Hard Negative Mining via Isometric Approximation Theorem

Albert Xu, Jhih-Yi Hsieh, Bhaskar Vundurthy et al.

Score Regularized Policy Optimization through Diffusion Behavior

Huayu Chen, Cheng Lu, Zhengyi Wang et al.

WildChat: 1M ChatGPT Interaction Logs in the Wild

Wenting Zhao, Xiang Ren, Jack Hessel et al.

Be Aware of the Neighborhood Effect: Modeling Selection Bias under Interference

Haoxuan Li, Chunyuan Zheng, Sihao Ding et al.

DAM: Towards a Foundation Model for Forecasting

Luke Darlow, Qiwen Deng, Ahmed Hassan et al.

Let 2D Diffusion Model Know 3D-Consistency for Robust Text-to-3D Generation

Junyoung Seo, Wooseok Jang, Min-Seop Kwak 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.

Vocos: Closing the gap between time-domain and Fourier-based neural vocoders for high-quality audio synthesis

Hubert Siuzdak

Robust NAS under adversarial training: benchmark, theory, and beyond

Yongtao Wu, Fanghui Liu, Carl-Johann Simon-Gabriel et al.

SE(3)-Stochastic Flow Matching for Protein Backbone Generation

Joey Bose, Tara Akhound-Sadegh, Guillaume Huguet 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

Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL

Hao Sun, Alihan Hüyük, Mihaela van der Schaar

ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference

Krzysztof Kacprzyk, Samuel Holt, Jeroen Berrevoets et al.

InstaFlow: One Step is Enough for High-Quality Diffusion-Based Text-to-Image Generation

Xingchao Liu, Xiwen Zhang, Jianzhu Ma 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.