Most Cited 2024 "equivariant neural fields" Papers

Guaranteed Approximation Bounds for Mixed-Precision Neural Operators

Renbo Tu, Colin White, Jean Kossaifi et al.

Lifting Architectural Constraints of Injective Flows

Peter Sorrenson, Felix Draxler, Armand Rousselot et al.

Aux-NAS: Exploiting Auxiliary Labels with Negligibly Extra Inference Cost

Yuan Gao, WEIZHONG ZHANG, Wenhan Luo et al.

Language Model Self-improvement by Reinforcement Learning Contemplation

Jing-Cheng Pang, Pengyuan Wang, Kaiyuan Li et al.

Fast Updating Truncated SVD for Representation Learning with Sparse Matrices

Haoran Deng, Yang Yang, Jiahe Li et al.

SOInter: A Novel Deep Energy-Based Interpretation Method for Explaining Structured Output Models

S. Fatemeh Seyyedsalehi, Mahdieh Baghshah, Hamid Rabiee

Sparse Spiking Neural Network: Exploiting Heterogeneity in Timescales for Pruning Recurrent SNN

Biswadeep Chakraborty, Beomseok Kang, Harshit Kumar et al.

Policy Rehearsing: Training Generalizable Policies for Reinforcement Learning

Chengxing Jia, Chen-Xiao Gao, Hao Yin et al.

ModernTCN: A Modern Pure Convolution Structure for General Time Series Analysis

DongHao Luo, Xue Wang

Prototypical Information Bottlenecking and Disentangling for Multimodal Cancer Survival Prediction

Yilan Zhang, Yingxue XU, Jianqi Chen et al.

On the Role of General Function Approximation in Offline Reinforcement Learning

Chenjie Mao, Qiaosheng Zhang, Zhen Wang et al.

Learning Delays in Spiking Neural Networks using Dilated Convolutions with Learnable Spacings

Ilyass Hammouamri, Ismail Khalfaoui Hassani, Timothée Masquelier

The Generative AI Paradox: “What It Can Create, It May Not Understand”

Peter West, Ximing Lu, Nouha Dziri et al.

The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning

Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu et al.

Phenomenal Yet Puzzling: Testing Inductive Reasoning Capabilities of Language Models with Hypothesis Refinement

Linlu Qiu, Liwei Jiang, Ximing Lu et al.

Evaluating Large Language Models at Evaluating Instruction Following

Zhiyuan Zeng, Jiatong Yu, Tianyu Gao et al.

Sheared LLaMA: Accelerating Language Model Pre-training via Structured Pruning

Mengzhou Xia, Tianyu Gao, Zhiyuan Zeng et al.

The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction

Pratyusha Sharma, Jordan Ash, Dipendra Kumar Misra

Learning Grounded Action Abstractions from Language

Lio Wong, Jiayuan Mao, Pratyusha Sharma et al.

Scaling Laws for Sparsely-Connected Foundation Models

Elias Frantar, Carlos Riquelme Ruiz, Neil Houlsby et al.

From Sparse to Soft Mixtures of Experts

Joan Puigcerver, Carlos Riquelme Ruiz, Basil Mustafa et al.

iGraphMix: Input Graph Mixup Method for Node Classification

Jongwon Jeong, Hoyeop Lee, Hyui Geon Yoon et al.

Retrieval-Enhanced Contrastive Vision-Text Models

Ahmet Iscen, Mathilde Caron, Alireza Fathi et al.

Raidar: geneRative AI Detection viA Rewriting

Chengzhi Mao, Carl Vondrick, Hao Wang et al.

Function Vectors in Large Language Models

Eric Todd, Millicent Li, Arnab Sen Sharma et al.

Unified Language-Vision Pretraining in LLM with Dynamic Discrete Visual Tokenization

Yang Jin, Kun Xu, Kun Xu et al.

A Policy Gradient Method for Confounded POMDPs

Mao Hong, Zhengling Qi, Yanxun Xu

MUSTARD: Mastering Uniform Synthesis of Theorem and Proof Data

Yinya Huang, Xiaohan Lin, Zhengying Liu et al.

LEGO-Prover: Neural Theorem Proving with Growing Libraries

Haiming Wang, Huajian Xin, Chuanyang Zheng et al.

THOUGHT PROPAGATION: AN ANALOGICAL APPROACH TO COMPLEX REASONING WITH LARGE LANGUAGE MODELS

Junchi Yu, Ran He, Rex Ying

GPT-4 Is Too Smart To Be Safe: Stealthy Chat with LLMs via Cipher

Youliang Yuan, Wenxiang Jiao, Wenxuan Wang et al.

On the Humanity of Conversational AI: Evaluating the Psychological Portrayal of LLMs

Jen-tse Huang, Wenxuan Wang, Eric John Li et al.

Accurate Retraining-free Pruning for Pretrained Encoder-based Language Models

Seungcheol Park, Hojun Choi, U Kang

INViTE: INterpret and Control Vision-Language Models with Text Explanations

Haozhe Chen, Junfeng Yang, Carl Vondrick et al.

Effective pruning of web-scale datasets based on complexity of concept clusters

Amro Kamal, Evgenia Rusak, Kushal Tirumala et al.

Sin3DM: Learning a Diffusion Model from a Single 3D Textured Shape

Rundi Wu, Ruoshi Liu, Carl Vondrick et al.

Remote Sensing Vision-Language Foundation Models without Annotations via Ground Remote Alignment

Utkarsh Kumar Mall, Cheng Perng Phoo, Meilin Liu et al.

DiffEnc: Variational Diffusion with a Learned Encoder

Beatrix M. G. Nielsen, Anders Christensen, Andrea Dittadi et al.

GIM: Learning Generalizable Image Matcher From Internet Videos

Xuelun Shen, zhipeng cai, Wei Yin et al.

DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks

Kaijie Zhu, Jiaao Chen, Jindong Wang et al.

The Unreasonable Effectiveness of Linear Prediction as a Perceptual Metric

Daniel Severo, Lucas Theis, Johannes Ballé

FFB: A Fair Fairness Benchmark for In-Processing Group Fairness Methods

Xiaotian Han, Jianfeng Chi, Yu Chen et al.

SAN: Inducing Metrizability of GAN with Discriminative Normalized Linear Layer

Yuhta Takida, Masaaki Imaizumi, Takashi Shibuya et al.

Learning to Relax: Setting Solver Parameters Across a Sequence of Linear System Instances

Mikhail Khodak, Edmond Chow, Nina Balcan et al.

Self-supervised Pocket Pretraining via Protein Fragment-Surroundings Alignment

Bowen Gao, Yinjun JIA, Yuanle Mo et al.

Solving Diffusion ODEs with Optimal Boundary Conditions for Better Image Super-Resolution

Yiyang Ma, Huan Yang, Wenhan Yang et al.

Unleashing the Power of Pre-trained Language Models for Offline Reinforcement Learning

Ruizhe Shi, Yuyao Liu, Yanjie Ze et al.

Rayleigh Quotient Graph Neural Networks for Graph-level Anomaly Detection

Xiangyu Dong, Xingyi Zhang, Sibo WANG

DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning

Jing Xiong, Zixuan Li, Chuanyang Zheng et al.

MetaGPT: Meta Programming for A Multi-Agent Collaborative Framework

Sirui Hong, Mingchen Zhuge, Jonathan Chen et al.

In-context Autoencoder for Context Compression in a Large Language Model

Tao Ge, Hu Jing, Lei Wang et al.

GenCorres: Consistent Shape Matching via Coupled Implicit-Explicit Shape Generative Models

Haitao Yang, Xiangru Huang, Bo Sun et al.

Hard-Constrained Deep Learning for Climate Downscaling

Paula Harder, Alex Hernandez-Garcia, Venkatesh Ramesh et al.

Information Bottleneck Analysis of Deep Neural Networks via Lossy Compression

Ivan Butakov, Aleksandr Tolmachev, Sofia Malanchuk et al.

ZipIt! Merging Models from Different Tasks without Training

George Stoica, Daniel Bolya, Jakob Bjorner et al.

Dynamic Sparse No Training: Training-Free Fine-tuning for Sparse LLMs

Yuxin Zhang, Lirui Zhao, Mingbao Lin et al.

MIntRec2.0: A Large-scale Benchmark Dataset for Multimodal Intent Recognition and Out-of-scope Detection in Conversations

Hanlei Zhang, Xin Wang, Hua Xu et al.

RLCD: Reinforcement Learning from Contrastive Distillation for LM Alignment

Kevin Yang, Dan Klein, Asli Celikyilmaz et al.

Localizing and Editing Knowledge In Text-to-Image Generative Models

Samyadeep Basu, Nanxuan Zhao, Vlad Morariu et al.

Efficient Dynamics Modeling in Interactive Environments with Koopman Theory

Arnab Mondal, Siba Smarak Panigrahi, Sai Rajeswar et al.

Generative Learning for Financial Time Series with Irregular and Scale-Invariant Patterns

Hongbin Huang, Minghua Chen, Xiao Qiao

Linear attention is (maybe) all you need (to understand Transformer optimization)

Kwangjun Ahn, Xiang Cheng, Minhak Song et al.

Scalable Diffusion for Materials Generation

Sherry Yang, Kwanghwan Cho, Amil Merchant et al.

MG-TSD: Multi-Granularity Time Series Diffusion Models with Guided Learning Process

Xinyao Fan, Yueying Wu, Chang XU et al.

RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches

Jiayuan Gu, Sean Kirmani, Paul Wohlhart et al.

Simplicial Representation Learning with Neural $k$-Forms

Kelly Maggs, Celia Hacker, Bastian Rieck

HAZARD Challenge: Embodied Decision Making in Dynamically Changing Environments

Qinhong Zhou, Sunli Chen, Yisong Wang et al.

Efficient Multi-agent Reinforcement Learning by Planning

Qihan Liu, Jianing Ye, Xiaoteng Ma et al.

DSPy: Compiling Declarative Language Model Calls into State-of-the-Art Pipelines

Omar Khattab, Arnav Singhvi, Paridhi Maheshwari et al.

On the Stability of Iterative Retraining of Generative Models on their own Data

Quentin Bertrand, Joey Bose, Alexandre Duplessis et al.

A Study of Bayesian Neural Network Surrogates for Bayesian Optimization

Yucen Li, Tim G. J. Rudner, Andrew Gordon Wilson

Fine-Tuned Language Models Generate Stable Inorganic Materials as Text

Nate Gruver, Anuroop Sriram, Andrea Madotto et al.

Prediction Error-based Classification for Class-Incremental Learning

Michał Zając, Tinne Tuytelaars, Gido M van de Ven

Deep Geodesic Canonical Correlation Analysis for Covariance-Based Neuroimaging Data

Ce Ju, Reinmar Kobler, Liyao Tang et al.

Beyond Weisfeiler-Lehman: A Quantitative Framework for GNN Expressiveness

Bohang Zhang, Jingchu Gai, Yiheng Du et al.

Adapting to Distribution Shift by Visual Domain Prompt Generation

Zhixiang Chi, Li Gu, Tao Zhong et al.

ImplicitSLIM and How it Improves Embedding-based Collaborative Filtering

Ilya Shenbin, Sergey Nikolenko

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Position: Towards Unified Alignment Between Agents, Humans, and Environment

Zonghan Yang, an liu, Zijun Liu et al.

Navigating Complexity: Toward Lossless Graph Condensation via Expanding Window Matching

Yuchen Zhang, Tianle Zhang, Kai Wang et al.

Fair Off-Policy Learning from Observational Data

Dennis Frauen, Valentyn Melnychuk, Stefan Feuerriegel

Consistent Submodular Maximization

PAUL DUETTING, Federico Fusco, Silvio Lattanzi et al.

Relaxing the Accurate Imputation Assumption in Doubly Robust Learning for Debiased Collaborative Filtering

Haoxuan Li, Chunyuan Zheng, Shuyi Wang et al.

Automated Statistical Model Discovery with Language Models

Michael Li, Emily Fox, Noah Goodman

Model-based Reinforcement Learning for Confounded POMDPs

Mao Hong, Zhengling Qi, Yanxun Xu

Position: A Call for Embodied AI

Giuseppe Paolo, Jonas Gonzalez-Billandon, Balázs Kégl

Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference

Wei-Lin Chiang, Lianmin Zheng, Ying Sheng et al.

WARM: On the Benefits of Weight Averaged Reward Models

Alexandre Rame, Nino Vieillard, Léonard Hussenot et al.

MusicRL: Aligning Music Generation to Human Preferences

Geoffrey Cideron, Sertan Girgin, Mauro Verzetti et al.

Nash Learning from Human Feedback

REMI MUNOS, Michal Valko, Daniele Calandriello et al.

LLM and Simulation as Bilevel Optimizers: A New Paradigm to Advance Physical Scientific Discovery

Pingchuan Ma, Johnson Tsun-Hsuan Wang, Minghao Guo et al.

Kernel-Based Evaluation of Conditional Biological Sequence Models

Pierre Glaser, Steffan Paul, Alissa M. Hummer et al.

TinyTrain: Resource-Aware Task-Adaptive Sparse Training of DNNs at the Data-Scarce Edge

Young Kwon, Rui Li, Stylianos Venieris et al.

Learning Associative Memories with Gradient Descent

Vivien Cabannnes, Berfin Simsek, Alberto Bietti

InfoNet: Neural Estimation of Mutual Information without Test-Time Optimization

Zhengyang Hu, Song Kang, Qunsong Zeng et al.

Calibration Bottleneck: Over-compressed Representations are Less Calibratable

Deng-Bao Wang, Min-Ling Zhang

Discovering Environments with XRM

Mohammad Pezeshki, Diane Bouchacourt, Mark Ibrahim et al.

Batch and match: black-box variational inference with a score-based divergence

Diana Cai, Chirag Modi, Loucas Pillaud-Vivien et al.

Transformers are SSMs: Generalized Models and Efficient Algorithms Through Structured State Space Duality

Tri Dao, Albert Gu

Combinatorial Approximations for Cluster Deletion: Simpler, Faster, and Better

Vicente Balmaseda, Ying Xu, Yixin Cao et al.

MVMoE: Multi-Task Vehicle Routing Solver with Mixture-of-Experts

Jianan Zhou, Zhiguang Cao, Yaoxin Wu et al.

Hybrid$^2$ Neural ODE Causal Modeling and an Application to Glycemic Response

Junyi Zou, Matthew Levine, Dessi Zaharieva et al.

Stereographic Spherical Sliced Wasserstein Distances

Huy Tran, Yikun Bai, Abihith Kothapalli et al.

Distribution Alignment Optimization through Neural Collapse for Long-tailed Classification

Jintong Gao, He Zhao, Dandan Guo et al.

How Learning by Reconstruction Produces Uninformative Features For Perception

Randall Balestriero, Yann LeCun

Effects of Exponential Gaussian Distribution on (Double Sampling) Randomized Smoothing

Youwei Shu, Xi Xiao, Derui Wang et al.

Sparse Inducing Points in Deep Gaussian Processes: Enhancing Modeling with Denoising Diffusion Variational Inference

JIAN XU, Delu Zeng, John Paisley

Fool Your (Vision and) Language Model with Embarrassingly Simple Permutations

Yongshuo Zong, Tingyang Yu, Ruchika Chavhan et al.

DRED: Zero-Shot Transfer in Reinforcement Learning via Data-Regularised Environment Design

Samuel Garcin, James Doran, Shangmin Guo et al.

Planning, Fast and Slow: Online Reinforcement Learning with Action-Free Offline Data via Multiscale Planners

Chengjie Wu, Hao Hu, yiqin yang et al.

Balanced Data, Imbalanced Spectra: Unveiling Class Disparities with Spectral Imbalance

Chiraag Kaushik, Ran Liu, Chi-Heng Lin et al.

The good, the bad and the ugly sides of data augmentation: An implicit spectral regularization perspective

Chi-Heng Lin, Chiraag Kaushik, Eva Dyer et al.

Active Preference Learning for Large Language Models

William Muldrew, Peter Hayes, Mingtian Zhang et al.

CodeIt: Self-Improving Language Models with Prioritized Hindsight Replay

Natasha Butt, Blazej Manczak, Auke Wiggers et al.

Variational Partial Group Convolutions for Input-Aware Partial Equivariance of Rotations and Color-Shifts

Hyunsu Kim, Ye Gon Kim, Hongseok Yang et al.

Incorporating Information into Shapley Values: Reweighting via a Maximum Entropy Approach

Darya Biparva, Donatello Materassi

Position: Why We Must Rethink Empirical Research in Machine Learning

Moritz Herrmann, F. Julian D. Lange, Katharina Eggensperger et al.

HarmoDT: Harmony Multi-Task Decision Transformer for Offline Reinforcement Learning

Shengchao Hu, Ziqing Fan, Li Shen et al.

Q-value Regularized Transformer for Offline Reinforcement Learning

Shengchao Hu, Ziqing Fan, Chaoqin Huang et al.

Locally Estimated Global Perturbations are Better than Local Perturbations for Federated Sharpness-aware Minimization

Ziqing Fan, Shengchao Hu, Jiangchao Yao et al.

Boundary Exploration for Bayesian Optimization With Unknown Physical Constraints

Yunsheng Tian, Ane Zuniga, Xinwei Zhang et al.

Understanding Reasoning Ability of Language Models From the Perspective of Reasoning Paths Aggregation

Xinyi Wang, Alfonso Amayuelas, Kexun Zhang et al.

Peeking with PEAK: Sequential, Nonparametric Composite Hypothesis Tests for Means of Multiple Data Streams

Brian Cho, Kyra Gan, Nathan Kallus

From Vision to Audio and Beyond: A Unified Model for Audio-Visual Representation and Generation

Kun Su, Xiulong Liu, Eli Shlizerman

Multi-group Learning for Hierarchical Groups

Samuel Deng, Daniel Hsu

Fast Decision Boundary based Out-of-Distribution Detector

Litian Liu, Yao Qin

Ensemble Pruning for Out-of-distribution Generalization

Fengchun Qiao, Xi Peng

Diffuse, Sample, Project: Plug-And-Play Controllable Graph Generation

Kartik Sharma, Srijan Kumar, Rakshit Trivedi

On the Asymptotic Distribution of the Minimum Empirical Risk

Jacob Westerhout, TrungTin Nguyen, Xin Guo et al.

RL-VLM-F: Reinforcement Learning from Vision Language Foundation Model Feedback

Yufei Wang, Zhanyi Sun, Jesse Zhang et al.

Exploiting Code Symmetries for Learning Program Semantics

Kexin Pei, Weichen Li, Qirui Jin et al.

Identification and Estimation for Nonignorable Missing Data: A Data Fusion Approach

Zixiao Wang, AmirEmad Ghassami, Ilya Shpitser

Encodings for Prediction-based Neural Architecture Search

Yash Akhauri, Mohamed Abdelfattah

Chain of Code: Reasoning with a Language Model-Augmented Code Emulator

Chengshu Li, Jacky Liang, Andy Zeng et al.

Towards Compositionality in Concept Learning

Adam Stein, Aaditya Naik, Yinjun Wu et al.

A Minimaximalist Approach to Reinforcement Learning from Human Feedback

Gokul Swamy, Christoph Dann, Rahul Kidambi et al.

Language Agent Tree Search Unifies Reasoning, Acting, and Planning in Language Models

Andy Zhou, Kai Yan, Michal Shlapentokh-Rothman et al.

Image Hijacks: Adversarial Images can Control Generative Models at Runtime

Luke Bailey, Euan Ong, Stuart Russell et al.

TENG: Time-Evolving Natural Gradient for Solving PDEs With Deep Neural Nets Toward Machine Precision

Zhuo Chen, Jacob McCarran, Esteban Vizcaino et al.

Decomposed Linear Dynamical Systems (dLDS) for learning the latent components of neural dynamics

Noga Mudrik, Yenho Chen, Eva Yezerets et al.

Behavior Generation with Latent Actions

Seungjae Lee, Yibin Wang, Haritheja Etukuru et al.

Measures of diversity and space-filling designs for categorical data

AstraZeneca Pharmaceutica, Emilio Domínguez-Sánchez, Merwan Barlier et al.

Pre-Training Protein Bi-level Representation Through Span Mask Strategy On 3D Protein Chains

Jiale Zhao, Wanru Zhuang, Jia Song et al.

QuRating: Selecting High-Quality Data for Training Language Models

Alexander Wettig, Aatmik Gupta, Saumya Malik et al.

On the Maximal Local Disparity of Fairness-Aware Classifiers

Jinqiu Jin, Haoxuan Li, Fuli Feng

Conditional Common Entropy for Instrumental Variable Testing and Partial Identification

Ziwei Jiang, Murat Kocaoglu

On PI Controllers for Updating Lagrange Multipliers in Constrained Optimization

Motahareh Sohrabi, Juan Ramirez, Tianyue Zhang et al.

Benchmarking Deletion Metrics with the Principled Explanations

Yipei Wang, Xiaoqian Wang

Online Matrix Completion: A Collaborative Approach with Hott Items

Dheeraj Baby, Soumyabrata Pal

Scaling Laws for Fine-Grained Mixture of Experts

Jan Ludziejewski, Jakub Krajewski, Kamil Adamczewski et al.

Benign Overfitting in Adversarial Training of Neural Networks

Yunjuan Wang, Kaibo Zhang, Raman Arora

Survival Kernets: Scalable and Interpretable Deep Kernel Survival Analysis with an Accuracy Guarantee

George Chen

Sample as you Infer: Predictive Coding with Langevin Dynamics

Umais Zahid, Qinghai Guo, Zafeirios Fountas

NeWRF: A Deep Learning Framework for Wireless Radiation Field Reconstruction and Channel Prediction

Haofan Lu, Christopher Vattheuer, Baharan Mirzasoleiman et al.

Efficient PAC Learnability of Dynamical Systems Over Multilayer Networks

Zirou Qiu, Abhijin Adiga, Madhav Marathe et al.

How Language Model Hallucinations Can Snowball

Muru Zhang, Ofir Press, William Merrill et al.

APT: Adaptive Pruning and Tuning Pretrained Language Models for Efficient Training and Inference

Bowen Zhao, Hannaneh Hajishirzi, Qingqing Cao

Extracting Training Data From Document-Based VQA Models

Francesco Pinto, Nathalie Rauschmayr, Florian Tramer et al.

MindEye2: Shared-Subject Models Enable fMRI-To-Image With 1 Hour of Data

Paul Scotti, Mihir Tripathy, Cesar Kadir Torrico Villanueva et al.

Prediction Accuracy of Learning in Games : Follow-the-Regularized-Leader meets Heisenberg

Yi Feng, Georgios Piliouras, Xiao Wang

PARCv2: Physics-aware Recurrent Convolutional Neural Networks for Spatiotemporal Dynamics Modeling

Phong Nguyen, Xinlun Cheng, Shahab Azarfar et al.

Unsupervised Concept Discovery Mitigates Spurious Correlations

Md Rifat Arefin, Yan Zhang, Aristide Baratin et al.

Scalable AI Safety via Doubly-Efficient Debate

Jonah Brown-Cohen, Geoffrey Irving, Georgios Piliouras

GeoMFormer: A General Architecture for Geometric Molecular Representation Learning

Tianlang Chen, Shengjie Luo, Di He et al.

Model Assessment and Selection under Temporal Distribution Shift

Elise Han, Chengpiao Huang, Kaizheng Wang

The Fundamental Limits of Least-Privilege Learning

Theresa Stadler, Bogdan Kulynych, Michael Gastpar et al.

Sequential Disentanglement by Extracting Static Information From A Single Sequence Element

Nimrod Berman, Ilan Naiman, Idan Arbiv et al.

Minimizing $f$-Divergences by Interpolating Velocity Fields

Song Liu, Jiahao Yu, Jack Simons et al.

Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models

Louis Sharrock, Jack Simons, Song Liu et al.

Bridging Mini-Batch and Asymptotic Analysis in Contrastive Learning: From InfoNCE to Kernel-Based Losses

Panagiotis Koromilas, Giorgos Bouritsas, Theodoros Giannakopoulos et al.

Subgoal-based Demonstration Learning for Formal Theorem Proving

Xueliang Zhao, Wenda Li, Lingpeng Kong

Vector Quantization Pretraining for EEG Time Series with Random Projection and Phase Alignment

Haokun Gui, Xiucheng Li, Xinyang Chen

Emergence of In-Context Reinforcement Learning from Noise Distillation

Ilya Zisman, Vladislav Kurenkov, Alexander Nikulin et al.

Any-Precision LLM: Low-Cost Deployment of Multiple, Different-Sized LLMs

Yeonhong Park, Jake Hyun, SangLyul Cho et al.

Robust Universal Adversarial Perturbations

Changming Xu, Gagandeep Singh

Low-Cost High-Power Membership Inference Attacks

Sajjad Zarifzadeh, Philippe Liu, Reza Shokri

Towards Modular LLMs by Building and Reusing a Library of LoRAs

Oleksiy Ostapenko, Zhan Su, Edoardo Ponti et al.

Early Time Classification with Accumulated Accuracy Gap Control

Liran Ringel, Regev Cohen, Daniel Freedman et al.

Evaluating Instrument Validity using the Principle of Independent Mechanisms

Patrick F. Burauel

Unified Generation, Reconstruction, and Representation: Generalized Diffusion with Adaptive Latent Encoding-Decoding

Guangyi Liu, Yu Wang, Zeyu Feng et al.

CogBench: a large language model walks into a psychology lab

Julian Coda-Forno, Marcel Binz, Jane Wang et al.

Human-like Category Learning by Injecting Ecological Priors from Large Language Models into Neural Networks

Akshay Kumar Jagadish, Julian Coda-Forno, Mirko Thalmann et al.

ConvNet vs Transformer, Supervised vs CLIP: Beyond ImageNet Accuracy

Kirill Vishniakov, Zhiqiang Shen, Zhuang Liu

Consistent Diffusion Meets Tweedie: Training Exact Ambient Diffusion Models with Noisy Data

Giannis Daras, Alexandros Dimakis, Constantinos Daskalakis

Optimally Improving Cooperative Learning in a Social Setting

Shahrzad Haddadan, Cheng Xin, Jie Gao

$\texttt{MoE-RBench}$: Towards Building Reliable Language Models with Sparse Mixture-of-Experts

Guanjie Chen, Xinyu Zhao, Tianlong Chen et al.

Simple linear attention language models balance the recall-throughput tradeoff

Simran Arora, Sabri Eyuboglu, Michael Zhang et al.

Principled Preferential Bayesian Optimization

Wenjie Xu, Wenbin Wang, Yuning Jiang et al.

SiT: Symmetry-invariant Transformers for Generalisation in Reinforcement Learning

Matthias Weissenbacher, Rishabh Agarwal, Yoshinobu Kawahara

On Positivity Condition for Causal Inference

Inwoo Hwang, Yesong Choe, Yeahoon Kwon et al.

Dynamic Memory Compression: Retrofitting LLMs for Accelerated Inference

Piotr Nawrot, Adrian Łańcucki, Marcin Chochowski et al.

Linguistic Calibration of Long-Form Generations

Neil Band, Xuechen Li, Tengyu Ma et al.

A Unified Framework for Learning with Nonlinear Model Classes from Arbitrary Linear Samples

Ben Adcock, Juan Cardenas, Nick Dexter

Slicedit: Zero-Shot Video Editing With Text-to-Image Diffusion Models Using Spatio-Temporal Slices

Nathaniel Cohen, Vladimir Kulikov, Matan Kleiner et al.

The Expressive Power of Path-Based Graph Neural Networks

Caterina Graziani, Tamara Drucks, Fabian Jogl et al.

Scalable High-Resolution Pixel-Space Image Synthesis with Hourglass Diffusion Transformers

Katherine Crowson, Stefan Baumann, Alex Birch et al.

Environment Design for Inverse Reinforcement Learning

Thomas Kleine Buening, Victor Villin, Christos Dimitrakakis

Stable Differentiable Causal Discovery

Achille Nazaret, Justin Hong, Elham Azizi et al.

Towards Optimal Adversarial Robust Q-learning with Bellman Infinity-error

Haoran Li, Zicheng Zhang, Wang Luo et al.

Can We Remove the Square-Root in Adaptive Gradient Methods? A Second-Order Perspective

Wu Lin, Felix Dangel, Runa Eschenhagen et al.