Most Cited ICLR "intent-aligned systems" Papers
6,124 papers found • Page 20 of 31
Conference
MovingParts: Motion-based 3D Part Discovery in Dynamic Radiance Field
Kaizhi Yang, Xiaoshuai Zhang, Zhiao Huang et al.
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
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.
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.
Query-Dependent Prompt Evaluation and Optimization with Offline Inverse RL
Hao Sun, Alihan Hüyük, Mihaela van der Schaar
Towards Transparent Time Series Forecasting
Krzysztof Kacprzyk, Tennison Liu, Mihaela van der Schaar
Traveling Waves Encode The Recent Past and Enhance Sequence Learning
T. Anderson Keller, Lyle Muller, Terrence Sejnowski et al.
GROOT: Learning to Follow Instructions by Watching Gameplay Videos
Shaofei Cai, Bowei Zhang, Zihao Wang et al.
FROSTER: Frozen CLIP is A Strong Teacher for Open-Vocabulary Action Recognition
Xiaohu Huang, Hao Zhou, Kun Yao et al.
Continual Learning in the Presence of Spurious Correlations: Analyses and a Simple Baseline
Donggyu Lee, Sangwon Jung, Taesup Moon
Data Debugging with Shapley Importance over Machine Learning Pipelines
Bojan Karlaš, David Dao, Matteo Interlandi et al.
Empirical Likelihood for Fair Classification
Pangpang Liu, Yichuan Zhao
SAFLEX: Self-Adaptive Augmentation via Feature Label Extrapolation
Mucong Ding, Bang An, Yuancheng Xu et al.
Deep Reinforcement Learning for Modelling Protein Complexes
Ziqi Gao, Tao Feng, Jiaxuan You et al.
LRR: Language-Driven Resamplable Continuous Representation against Adversarial Tracking Attacks
Jianlang Chen, Xuhong Ren, Qing Guo et al.
Learning to Embed Time Series Patches Independently
Seunghan Lee, Taeyoung Park, Kibok Lee
Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood
yaxuan zhu, Jianwen Xie, Yingnian Wu et al.
Balancing Act: Constraining Disparate Impact in Sparse Models
Meraj Hashemizadeh, Juan Ramirez, Rohan Sukumaran et al.
Flow Matching on General Geometries
Ricky T. Q. Chen, Yaron Lipman
LipVoicer: Generating Speech from Silent Videos Guided by Lip Reading
Yochai Yemini, Aviv Shamsian, Lior Bracha et al.
Bespoke Solvers for Generative Flow Models
Neta Shaul, Juan Perez, Ricky T. Q. Chen et al.
DittoGym: Learning to Control Soft Shape-Shifting Robots
Suning Huang, Boyuan Chen, Huazhe Xu et al.
Zero-Shot Robotic Manipulation with Pre-Trained Image-Editing Diffusion Models
Kevin Black, Mitsuhiko Nakamoto, Pranav Atreya et al.
VersVideo: Leveraging Enhanced Temporal Diffusion Models for Versatile Video Generation
Jinxi Xiang, Ricong Huang, Jun Zhang et al.
BrainLM: A foundation model for brain activity recordings
Josue Ortega Caro, Antonio Henrique de Oliveira Fonseca, Syed Rizvi et al.
Fourier Transporter: Bi-Equivariant Robotic Manipulation in 3D
Haojie Huang, Owen Howell, Dian Wang et al.
Faithful Explanations of Black-box NLP Models Using LLM-generated Counterfactuals
Yair Gat, Nitay Calderon, Amir Feder et al.
Large Language Models Cannot Self-Correct Reasoning Yet
Jie Huang, Xinyun Chen, Swaroop Mishra et al.
H-GAP: Humanoid Control with a Generalist Planner
Zhengyao Jiang, Yingchen Xu, Nolan Wagener et al.
Explaining Kernel Clustering via Decision Trees
Maximilian Fleissner, Leena Chennuru Vankadara, Debarghya Ghoshdastidar
Select to Perfect: Imitating desired behavior from large multi-agent data
Tim Franzmeyer, Edith Elkind, Philip Torr et al.
Integrating Planning and Deep Reinforcement Learning via Automatic Induction of Task Substructures
Jung-Chun Liu, Chi-Hsien Chang, Shao-Hua Sun et al.
GIO: Gradient Information Optimization for Training Dataset Selection
Dante Everaert, Christopher Potts
SLiMe: Segment Like Me
Aliasghar Khani, Saeid Asgari, Aditya Sanghi et al.
MathCoder: Seamless Code Integration in LLMs for Enhanced Mathematical Reasoning
Ke Wang, Houxing Ren, Aojun Zhou et al.
BadEdit: Backdooring Large Language Models by Model Editing
Yanzhou Li, Tianlin Li, Kangjie Chen et al.
Neural Monge Map estimation and its applications
Shaojun Ma, Yongxin Chen, Hao-Min Zhou et al.
Rethinking the Power of Graph Canonization in Graph Representation Learning with Stability
Zehao Dong, Muhan Zhang, Philip Payne et al.
On the Sample Complexity of Lipschitz Constant Estimation
Stephen Roberts, Julien Huang, Jan-Peter Calliess
Increasing Model Capacity for Free: A Simple Strategy for Parameter Efficient Fine-tuning
Haobo Song, Haobo SONG, Hao Zhao et al.
Image Background Serves as Good Proxy for Out-of-distribution Data
Sen Pei
FedTrans: Client-Transparent Utility Estimation for Robust Federated Learning
Mingkun Yang, Ran Zhu, Qing Wang et al.
CLEX: Continuous Length Extrapolation for Large Language Models
Guanzheng Chen, Xin Li, Zaiqiao Meng et al.
Combining Axes Preconditioners through Kronecker Approximation for Deep Learning
Venkata Sai Surya Subramanyam Duvvuri, Fnu Devvrit, Rohan Anil et al.
MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning
Xiang Yue, Xingwei Qu, Ge Zhang et al.
LEMON: Lossless model expansion
Yite Wang, Jiahao Su, Hanlin Lu et al.
Deceptive Fairness Attacks on Graphs via Meta Learning
Jian Kang, Yinglong Xia, Ross Maciejewski et al.
Optimal Sketching for Residual Error Estimation for Matrix and Vector Norms
Yi Li, Honghao Lin, David Woodruff
CompA: Addressing the Gap in Compositional Reasoning in Audio-Language Models
Sreyan Ghosh, Ashish Seth, Sonal Kumar et al.
Towards Robust Out-of-Distribution Generalization Bounds via Sharpness
Yingtian Zou, Kenji Kawaguchi, Yingnan Liu et al.
A Unified Sampling Framework for Solver Searching of Diffusion Probabilistic Models
Enshu Liu, Xuefei Ning, Huazhong Yang et al.
DiffusionSat: A Generative Foundation Model for Satellite Imagery
Samar Khanna, Patrick Liu, Linqi Zhou et al.
Denoising Diffusion Bridge Models
Linqi Zhou, Aaron Lou, Samar Khanna et al.
Causal Inference with Conditional Front-Door Adjustment and Identifiable Variational Autoencoder
Ziqi Xu, Debo Cheng, Jiuyong Li et al.
Impact of Computation in Integral Reinforcement Learning for Continuous-Time Control
Wenhan Cao, Wei Pan
Generalized Schrödinger Bridge Matching
Guan-Horng Liu, Yaron Lipman, Maximilian Nickel et al.
Repeated Random Sampling for Minimizing the Time-to-Accuracy of Learning
Patrik Okanovic, Roger Waleffe, Vasilis Mageirakos et al.
Privately Aligning Language Models with Reinforcement Learning
Fan Wu, Huseyin Inan, Arturs Backurs et al.
Let's Verify Step by Step
Hunter Lightman, Vineet Kosaraju, Yuri Burda et al.
Uncertainty Quantification via Stable Distribution Propagation
Felix Petersen, Aashwin Mishra, Hilde Kuehne et al.
LLMs Meet VLMs: Boost Open Vocabulary Object Detection with Fine-grained Descriptors
Sheng JIn, Xueying Jiang, Jiaxing Huang et al.
SKILL-MIX: a Flexible and Expandable Family of Evaluations for AI Models
Dingli Yu, Simran Kaur, Arushi Gupta et al.
LoTa-Bench: Benchmarking Language-oriented Task Planners for Embodied Agents
Jae-Woo Choi, Youngwoo Yoon, Youngwoo Yoon et al.
Fast-ELECTRA for Efficient Pre-training
Chengyu Dong, Liyuan Liu, Hao Cheng et al.
Skip-Attention: Improving Vision Transformers by Paying Less Attention
Shashank Venkataramanan, Amir Ghodrati, Yuki Asano et al.
Reasoning on Graphs: Faithful and Interpretable Large Language Model Reasoning
Linhao Luo, Yuan-Fang Li, Reza Haffari et al.
Fiber Monte Carlo
Nick Richardson, Deniz Oktay, Yaniv Ovadia et al.
A Framework and Benchmark for Deep Batch Active Learning for Regression
David Holzmüller, Viktor Zaverkin, Johannes Kästner et al.
ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation
Jiaming Liu, Senqiao Yang, Peidong Jia et al.
ToRA: A Tool-Integrated Reasoning Agent for Mathematical Problem Solving
Zhibin Gou, Zhihong Shao, Yeyun Gong et al.
Towards Robust Offline Reinforcement Learning under Diverse Data Corruption
Rui Yang, Han Zhong, Jiawei Xu et al.
Vanishing Gradients in Reinforcement Finetuning of Language Models
Noam Razin, Hattie Zhou, Omid Saremi et al.
Effective and Efficient Federated Tree Learning on Hybrid Data
Qinbin Li, Chulin Xie, Xiaojun Xu et al.
Boosting the Adversarial Robustness of Graph Neural Networks: An OOD Perspective
Kuan Li, YiWen Chen, Yang Liu et al.
SetCSE: Set Operations using Contrastive Learning of Sentence Embeddings
Kang Liu
Unsupervised Pretraining for Fact Verification by Language Model Distillation
Adrian Bazaga, Pietro Lio, Gos Micklem
Towards Assessing and Benchmarking Risk-Return Tradeoff of Off-Policy Evaluation
Haruka Kiyohara, Ren Kishimoto, Kosuke Kawakami et al.
Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining
Licong Lin, Yu Bai, Song Mei
Improving Convergence and Generalization Using Parameter Symmetries
Bo Zhao, Robert M. Gower, Robin Walters et al.
COLEP: Certifiably Robust Learning-Reasoning Conformal Prediction via Probabilistic Circuits
Mintong Kang, Nezihe Merve Gürel, Linyi Li et al.
Manifold Preserving Guided Diffusion
Yutong He, Naoki Murata, Chieh-Hsin Lai et al.
Threaten Spiking Neural Networks through Combining Rate and Temporal Information
Zecheng Hao, Tong Bu, Xinyu Shi et al.
Federated Recommendation with Additive Personalization
Zhiwei Li, Guodong Long, Tianyi Zhou
Correlated Noise Provably Beats Independent Noise for Differentially Private Learning
Christopher Choquette-Choo, Krishnamurthy Dvijotham, Krishna Pillutla et al.
On the Stability of Expressive Positional Encodings for Graphs
Yinan Huang, William Lu, Joshua Robinson et al.
Evaluating Representation Learning on the Protein Structure Universe
Arian Jamasb, Alex Morehead, Chaitanya Joshi et al.
On the Hardness of Constrained Cooperative Multi-Agent Reinforcement Learning
Ziyi Chen, Yi Zhou, Heng Huang
Off-Policy Primal-Dual Safe Reinforcement Learning
Zifan Wu, Bo Tang, Qian Lin et al.
When should we prefer Decision Transformers for Offline Reinforcement Learning?
Prajjwal Bhargava, Rohan Chitnis, Alborz Geramifard et al.
ARM: Refining Multivariate Forecasting with Adaptive Temporal-Contextual Learning
Jiecheng Lu, Xu Han, Shihao Yang
SAS: Structured Activation Sparsification
Yusuke Sekikawa, Shingo Yashima
Threshold-Consistent Margin Loss for Open-World Deep Metric Learning
Qin ZHANG, Linghan Xu, Jun Fang et al.
Improved statistical and computational complexity of the mean-field Langevin dynamics under structured data
Atsushi Nitanda, Kazusato Oko, Taiji Suzuki et al.
Bridging Neural and Symbolic Representations with Transitional Dictionary Learning
Junyan Cheng, Peter Chin
Scale-Adaptive Diffusion Model for Complex Sketch Synthesis
Jijin Hu, Ke Li, Yonggang Qi et al.
Energy-conserving equivariant GNN for elasticity of lattice architected metamaterials
Ivan Grega, Ilyes Batatia, Gábor Csányi et al.
SALMON: Self-Alignment with Instructable Reward Models
Zhiqing Sun, Yikang Shen, Hongxin Zhang et al.
Get more for less: Principled Data Selection for Warming Up Fine-Tuning in LLMs
Feiyang Kang, Hoang Anh Just, Yifan Sun et al.
The Joint Effect of Task Similarity and Overparameterization on Catastrophic Forgetting — An Analytical Model
Daniel Goldfarb, Itay Evron, Nir Weinberger et al.
Compositional Preference Models for Aligning LMs
DONGYOUNG GO, Tomek Korbak, Germàn Kruszewski et al.
Diffusion Posterior Sampling for Linear Inverse Problem Solving: A Filtering Perspective
Zehao Dou, Yang Song
Demystifying Local & Global Fairness Trade-offs in Federated Learning Using Partial Information Decomposition
Faisal Hamman, Sanghamitra Dutta
Generative Modeling with Phase Stochastic Bridge
Tianrong Chen, Jiatao Gu, Laurent Dinh et al.
Tailoring Self-Rationalizers with Multi-Reward Distillation
Sahana Ramnath, Brihi Joshi, Skyler Hallinan et al.
Controlling Vision-Language Models for Multi-Task Image Restoration
Ziwei Luo, Fredrik K. Gustafsson, Zheng Zhao et al.
Measuring Vision-Language STEM Skills of Neural Models
Jianhao Shen, Ye Yuan, Srbuhi Mirzoyan et al.
Connecting Large Language Models with Evolutionary Algorithms Yields Powerful Prompt Optimizers
Qingyan Guo, Rui Wang, Junliang Guo et al.
NaturalSpeech 2: Latent Diffusion Models are Natural and Zero-Shot Speech and Singing Synthesizers
Kai Shen, Zeqian Ju, Xu Tan et al.
How connectivity structure shapes rich and lazy learning in neural circuits
Yuhan Helena Liu, Aristide Baratin, Jonathan Cornford et al.
NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks
Wenxi Wang, Yang Hu, Mohit Tiwari et al.
Revisiting Deep Audio-Text Retrieval Through the Lens of Transportation
Tien Manh Luong, Khai Nguyen, Nhat Ho et al.
Branch-GAN: Improving Text Generation with (not so) Large Language Models
Fredrik Carlsson, Johan Broberg, Erik Hillbom et al.
A unique M-pattern for micro-expression spotting in long videos
Jinxuan Wang, Shiting Xu, Tong Zhang
Internal Cross-layer Gradients for Extending Homogeneity to Heterogeneity in Federated Learning
Yun-Hin Chan, Rui Zhou, Running Zhao et al.
iTransformer: Inverted Transformers Are Effective for Time Series Forecasting
Yong Liu, Tengge Hu, Haoran Zhang et al.
Stylized Offline Reinforcement Learning: Extracting Diverse High-Quality Behaviors from Heterogeneous Datasets
Yihuan Mao, Chengjie Wu, Xi Chen et al.
Demystifying Embedding Spaces using Large Language Models
Guy Tennenholtz, Yinlam Chow, ChihWei Hsu et al.
Closing the Gap between TD Learning and Supervised Learning - A Generalisation Point of View.
Raj Ghugare, Matthieu Geist, Glen Berseth et al.
Learning Thresholds with Latent Values and Censored Feedback
Jiahao Zhang, Tao Lin, Weiqiang Zheng et al.
Extending Power of Nature from Binary to Real-Valued Graph Learning in Real World
Chunshu Wu, Ruibing Song, Chuan Liu et al.
Guess & Sketch: Language Model Guided Transpilation
Celine Lee, Abdulrahman Mahmoud, Michal Kurek et al.
An Investigation of Representation and Allocation Harms in Contrastive Learning
Subha Maity, Mayank Agarwal, Mikhail Yurochkin et al.
Channel Vision Transformers: An Image Is Worth 1 x 16 x 16 Words
Yujia Bao, Srinivasan Sivanandan, THEOFANIS KARALETSOS
ReLU Strikes Back: Exploiting Activation Sparsity in Large Language Models
Iman Mirzadeh, Keivan Alizadeh-Vahid, Sachin Mehta et al.
Tractable MCMC for Private Learning with Pure and Gaussian Differential Privacy
Yingyu Lin, Yian Ma, Yu-Xiang Wang et al.
Jailbreak in pieces: Compositional Adversarial Attacks on Multi-Modal Language Models
Erfan Shayegani, Yue Dong, Nael Abu-Ghazaleh
Scalable Modular Network: A Framework for Adaptive Learning via Agreement Routing
Minyang Hu, Hong Chang, Bingpeng Ma et al.
Recursive Generalization Transformer for Image Super-Resolution
Zheng Chen, Yulun Zhang, Jinjin Gu et al.
Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data
Binghui Li, Yuanzhi Li
Treatment Effects Estimation By Uniform Transformer
Ruoqi Yu, Shulei Wang
Representation Deficiency in Masked Language Modeling
Yu Meng, Jitin Krishnan, Sinong Wang et al.
Sampling Multimodal Distributions with the Vanilla Score: Benefits of Data-Based Initialization
Frederic Koehler, Thuy-Duong Vuong
FedInverse: Evaluating Privacy Leakage in Federated Learning
DI WU, Jun Bai, Yiliao Song et al.
Neuron Activation Coverage: Rethinking Out-of-distribution Detection and Generalization
Yibing Liu, Chris Xing TIAN, Haoliang Li et al.
Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation
Xuefei Ning, Zinan Lin, Zixuan Zhou et al.
Neural Rate Control for Learned Video Compression
yiwei zhang, Guo Lu, Yunuo Chen et al.
Sliced Denoising: A Physics-Informed Molecular Pre-Training Method
yuyan ni, Shikun Feng, Wei-Ying Ma et al.
Poisoned Forgery Face: Towards Backdoor Attacks on Face Forgery Detection
Jiawei Liang, Siyuan Liang, Aishan Liu et al.
Free from Bellman Completeness: Trajectory Stitching via Model-based Return-conditioned Supervised Learning
Zhaoyi Zhou, Chuning Zhu, Runlong Zhou et al.
Simple Hierarchical Planning with Diffusion
Chang Chen, Fei Deng, Kenji Kawaguchi et al.
Dynamic Sparse Training with Structured Sparsity
Mike Lasby, Anna Golubeva, Utku Evci et al.
DENEVIL: TOWARDS DECIPHERING AND NAVIGATING THE ETHICAL VALUES OF LARGE LANGUAGE MODELS VIA INSTRUCTION LEARNING
Shitong Duan, Xiaoyuan Yi, Peng Zhang et al.
Robustifying State-space Models for Long Sequences via Approximate Diagonalization
Annan Yu, Arnur Nigmetov, Dmitriy Morozov et al.
Test-Time Adaptation with CLIP Reward for Zero-Shot Generalization in Vision-Language Models
Shuai Zhao, Xiaohan Wang, Linchao Zhu et al.
Efficient Inverse Multiagent Learning
Denizalp Goktas, Amy Greenwald, Sadie Zhao et al.
C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion
Hee Suk Yoon, Eunseop Yoon, Joshua Tian Jin Tee et al.
Plugin estimators for selective classification with out-of-distribution detection
Harikrishna Narasimhan, Aditya Krishna Menon, Wittawat Jitkrittum et al.
Adaptive Stochastic Gradient Algorithm for Black-box Multi-Objective Learning
Feiyang YE, YUEMING LYU, Xuehao Wang et al.
Intriguing Properties of Data Attribution on Diffusion Models
Xiaosen Zheng, Tianyu Pang, Chao Du et al.
Provably Efficient UCB-type Algorithms For Learning Predictive State Representations
Ruiquan Huang, Yingbin Liang, Jing Yang
Inner Classifier-Free Guidance and Its Taylor Expansion for Diffusion Models
Shikun Sun, Longhui Wei, Zhicai Wang et al.
Going Beyond Neural Network Feature Similarity: The Network Feature Complexity and Its Interpretation Using Category Theory
Yiting Chen, Zhanpeng Zhou, Junchi Yan
Learning Large DAGs is Harder than you Think: Many Losses are Minimal for the Wrong DAG
Jonas Seng, Matej Zečević, Devendra Singh Dhami et al.
Nearly $d$-Linear Convergence Bounds for Diffusion Models via Stochastic Localization
Joe Benton, Valentin De Bortoli, Arnaud Doucet et al.
Active Retrosynthetic Planning Aware of Route Quality
Luotian Yuan, Yemin Yu, Ying Wei et al.
Merge, Then Compress: Demystify Efficient SMoE with Hints from Its Routing Policy
Pingzhi Li, Zhenyu Zhang, Prateek Yadav et al.
Non-Exchangeable Conformal Risk Control
António Farinhas, Chrysoula Zerva, Dennis Ulmer et al.
Early Stopping Against Label Noise Without Validation Data
Suqin Yuan, Lei Feng, Tongliang Liu
Enhancing Transfer Learning with Flexible Nonparametric Posterior Sampling
Hyungi Lee, Giung Nam, Edwin Fong et al.
Neural Contractive Dynamical Systems
Hadi Beik Mohammadi, Søren Hauberg, Georgios Arvanitidis et al.
Energy-based Automated Model Evaluation
Ru Peng, Heming Zou, Haobo Wang et al.
Toward Optimal Policy Population Growth in Two-Player Zero-Sum Games
Stephen McAleer, John Banister Lanier, Kevin A. Wang et al.
Towards Robust and Efficient Cloud-Edge Elastic Model Adaptation via Selective Entropy Distillation
Yaofo Chen, Shuaicheng Niu, Yaowei Wang et al.
Beyond task performance: evaluating and reducing the flaws of large multimodal models with in-context-learning
Mustafa Shukor, Alexandre Rame, Corentin Dancette et al.
The Trickle-down Impact of Reward Inconsistency on RLHF
Lingfeng Shen, Lingfeng Shen, Sihao Chen et al.
Better Neural PDE Solvers Through Data-Free Mesh Movers
Peiyan Hu, Yue Wang, Zhi-Ming Ma
Memorization Capacity of Multi-Head Attention in Transformers
Sadegh Mahdavi, Renjie Liao, Christos Thrampoulidis
Domain-Inspired Sharpness-Aware Minimization Under Domain Shifts
Ruipeng Zhang, Ziqing Fan, Jiangchao Yao et al.
Maximum Likelihood Estimation is All You Need for Well-Specified Covariate Shift
Jiawei Ge, Shange Tang, Jianqing Fan et al.
A Sublinear Adversarial Training Algorithm
Yeqi Gao, Lianke Qin, Zhao Song et al.
Performance Gaps in Multi-view Clustering under the Nested Matrix-Tensor Model
Hugo Lebeau, Mohamed El Amine Seddik, José Henrique Goulart
ZeRO++: Extremely Efficient Collective Communication for Large Model Training
Guanhua Wang, Heyang Qin, Sam Jacobs et al.
CausalLM is not optimal for in-context learning
Nan Ding, Tomer Levinboim, Jialin Wu et al.
An Unforgeable Publicly Verifiable Watermark for Large Language Models
Aiwei Liu, Leyi Pan, Xuming Hu et al.
Class Probability Matching with Calibrated Networks for Label Shift Adaption
Hongwei Wen, Annika Betken, Hanyuan Hang
Memory-Assisted Sub-Prototype Mining for Universal Domain Adaptation
Yuxiang (YU-HSIANG) LAI, Yi Zhou, Xinghong Liu et al.
Ito Diffusion Approximation of Universal Ito Chains for Sampling, Optimization and Boosting
Aleksei Ustimenko, Aleksandr Beznosikov
Würstchen: An Efficient Architecture for Large-Scale Text-to-Image Diffusion Models
Pablo Pernías, Dominic Rampas, Mats L. Richter et al.
Sparse MoE with Language Guided Routing for Multilingual Machine Translation
Xinyu Zhao, Xuxi Chen, Yu Cheng et al.
Neural Architecture Retrieval
Xiaohuan Pei, Yanxi Li, Minjing Dong et al.
Neural SDF Flow for 3D Reconstruction of Dynamic Scenes
wei mao, Richard Hartley, Mathieu Salzmann et al.
Compressing LLMs: The Truth is Rarely Pure and Never Simple
AJAY JAISWAL, Zhe Gan, Xianzhi Du et al.
ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search
Yuchen Zhuang, Xiang Chen, Tong Yu et al.
LayoutNUWA: Revealing the Hidden Layout Expertise of Large Language Models
Zecheng Tang, Zecheng Tang, Chenfei Wu et al.
Learning Mean Field Games on Sparse Graphs: A Hybrid Graphex Approach
Christian Fabian, Kai Cui, Heinz Koeppl
Understanding In-Context Learning in Transformers and LLMs by Learning to Learn Discrete Functions
Satwik Bhattamishra, Arkil Patel, Phil Blunsom et al.
One-hot Generalized Linear Model for Switching Brain State Discovery
Chengrui Li, Soon Ho Kim, Chris Rodgers et al.
Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs
Ilan Naiman, N. Benjamin Erichson, Pu Ren et al.
Annealing Self-Distillation Rectification Improves Adversarial Training
Yu-Yu Wu, Hung-Jui Wang, Shang-Tse Chen
Simplifying, Stabilizing and Scaling Continuous-time Consistency Models
Cheng Lu, Yang Song
Rotation Has Two Sides: Evaluating Data Augmentation for Deep One-class Classification
Guodong Wang, Yunhong Wang, Xiuguo Bao et al.
Small-scale proxies for large-scale Transformer training instabilities
Mitchell Wortsman, Peter Liu, Lechao Xiao et al.
Lion Secretly Solves a Constrained Optimization: As Lyapunov Predicts
Lizhang Chen, Bo Liu, Kaizhao Liang et al.
Node2ket: Efficient High-Dimensional Network Embedding in Quantum Hilbert Space
Hao Xiong, Yehui Tang, Yunlin He et al.
Procedural Fairness Through Decoupling Objectionable Data Generating Components
Zeyu Tang, Jialu Wang, Yang Liu et al.
Scaling Supervised Local Learning with Augmented Auxiliary Networks
Chenxiang Ma, Jibin Wu, Chenyang Si et al.
Scalable Monotonic Neural Networks
Hyunho Kim, Jong-Seok Lee