ICLR Papers
6,124 papers found • Page 118 of 123
The Effect of Intrinsic Dataset Properties on Generalization: Unraveling Learning Differences Between Natural and Medical Images
Nicholas Konz, Maciej Mazurowski
The Expressive Leaky Memory Neuron: an Efficient and Expressive Phenomenological Neuron Model Can Solve Long-Horizon Tasks.
Aaron Spieler, Nasim Rahaman, Georg Martius et al.
The Expressive Power of Low-Rank Adaptation
Yuchen Zeng, Kangwook Lee
The Expressive Power of Transformers with Chain of Thought
William Merrill, Ashish Sabharwal
The False Promise of Imitating Proprietary Language Models
Arnav Gudibande, Eric Wallace, Charlie Snell et al.
The Generalization Gap in Offline Reinforcement Learning
Ishita Mediratta, Qingfei You, Minqi Jiang et al.
The Generative AI Paradox: “What It Can Create, It May Not Understand”
Peter West, Ximing Lu, Nouha Dziri et al.
The Hedgehog & the Porcupine: Expressive Linear Attentions with Softmax Mimicry
Michael Zhang, Kush Bhatia, Hermann Kumbong et al.
The Hidden Language of Diffusion Models
Hila Chefer, Oran Lang, Mor Geva et al.
The Human-AI Substitution game: active learning from a strategic labeler
Tom Yan, Chicheng Zhang
The importance of feature preprocessing for differentially private linear optimization
Ziteng Sun, Ananda Theertha Suresh, Aditya Krishna Menon
The Joint Effect of Task Similarity and Overparameterization on Catastrophic Forgetting — An Analytical Model
Daniel Goldfarb, Itay Evron, Nir Weinberger et al.
The Lipschitz-Variance-Margin Tradeoff for Enhanced Randomized Smoothing
Blaise Delattre, Alexandre Araujo, Quentin Barthélemy et al.
The LLM Surgeon
Tycho van der Ouderaa, Markus Nagel, Mart van Baalen et al.
The Marginal Value of Momentum for Small Learning Rate SGD
Runzhe Wang, Sadhika Malladi, Tianhao Wang et al.
The mechanistic basis of data dependence and abrupt learning in an in-context classification task
Gautam Reddy Nallamala
The Need for Speed: Pruning Transformers with One Recipe
Samir Khaki, Konstantinos Plataniotis
The optimality of kernel classifiers in Sobolev space
Jianfa Lai, zhifan Li, Dongming Huang et al.
Theoretical Analysis of Robust Overfitting for Wide DNNs: An NTK Approach
Shaopeng Fu, Di Wang
Theoretical Understanding of Learning from Adversarial Perturbations
Soichiro Kumano, Hiroshi Kera, Toshihiko Yamasaki
The Reasonableness Behind Unreasonable Translation Capability of Large Language Model
Tingchen Fu, lemao liu, Deng Cai et al.
The Reversal Curse: LLMs trained on “A is B” fail to learn “B is A”
Lukas Berglund, Meg Tong, Maximilian Kaufmann et al.
The Trickle-down Impact of Reward Inconsistency on RLHF
Lingfeng Shen, Lingfeng Shen, Sihao Chen et al.
The Truth is in There: Improving Reasoning in Language Models with Layer-Selective Rank Reduction
Pratyusha Sharma, Jordan Ash, Dipendra Kumar Misra
The Unlocking Spell on Base LLMs: Rethinking Alignment via In-Context Learning
Bill Yuchen Lin, Abhilasha Ravichander, Ximing Lu et al.
The Unreasonable Effectiveness of Linear Prediction as a Perceptual Metric
Daniel Severo, Lucas Theis, Johannes Ballé
The Update-Equivalence Framework for Decision-Time Planning
Samuel Sokota, Gabriele Farina, David Wu et al.
The Wasserstein Believer: Learning Belief Updates for Partially Observable Environments through Reliable Latent Space Models
Raphael Avalos, Florent Delgrange, Ann Nowe et al.
Think before you speak: Training Language Models With Pause Tokens
Sachin Goyal, Ziwei Ji, Ankit Singh Rawat et al.
Think-on-Graph: Deep and Responsible Reasoning of Large Language Model on Knowledge Graph
Jiashuo Sun, Chengjin Xu, Lumingyuan Tang et al.
Thin-Shell Object Manipulations With Differentiable Physics Simulations
Yian Wang, Juntian Zheng, Zhehuan Chen et al.
THOUGHT PROPAGATION: AN ANALOGICAL APPROACH TO COMPLEX REASONING WITH LARGE LANGUAGE MODELS
Junchi Yu, Ran He, Rex Ying
Threaten Spiking Neural Networks through Combining Rate and Temporal Information
Zecheng Hao, Tong Bu, Xinyu Shi et al.
Threshold-Consistent Margin Loss for Open-World Deep Metric Learning
Qin ZHANG, Linghan Xu, Jun Fang et al.
TiC-CLIP: Continual Training of CLIP Models
Saurabh Garg, Mehrdad Farajtabar, Hadi Pouransari et al.
Tight Rates in Supervised Outlier Transfer Learning
Mohammadreza Mousavi Kalan, Samory Kpotufe
Time-Efficient Reinforcement Learning with Stochastic Stateful Policies
Firas Al-Hafez, Guoping Zhao, Jan Peters et al.
Time Fairness in Online Knapsack Problems
Adam Lechowicz, Rik Sengupta, Bo Sun et al.
Time-LLM: Time Series Forecasting by Reprogramming Large Language Models
Ming Jin, Shiyu Wang, Lintao Ma et al.
TimeMixer: Decomposable Multiscale Mixing for Time Series Forecasting
Shiyu Wang, Haixu Wu, Xiaoming Shi et al.
Time Travel in LLMs: Tracing Data Contamination in Large Language Models
Shahriar Golchin, Mihai Surdeanu
Time-Varying Propensity Score to Bridge the Gap between the Past and Present
Rasool Fakoor, Jonas Mueller, Zachary Lipton et al.
T-MARS: Improving Visual Representations by Circumventing Text Feature Learning
Pratyush Maini, Sachin Goyal, Zachary Lipton et al.
To Grok or not to Grok: Disentangling Generalization and Memorization on Corrupted Algorithmic Datasets
Darshil Doshi, Aritra Das, Tianyu He et al.
TokenFlow: Consistent Diffusion Features for Consistent Video Editing
Michal Geyer, Omer Bar Tal, Shai Bagon et al.
Tool-Augmented Reward Modeling
Lei Li, Yekun Chai, Shuohuan Wang et al.
ToolChain*: Efficient Action Space Navigation in Large Language Models with A* Search
Yuchen Zhuang, Xiang Chen, Tong Yu et al.
ToolLLM: Facilitating Large Language Models to Master 16000+ Real-world APIs
Yujia Qin, Shihao Liang, Yining Ye et al.
Topic Modeling as Multi-Objective Contrastive Optimization
Thong Thanh Nguyen, Xiaobao Wu, Xinshuai Dong et al.
Topological data analysis on noisy quantum computers
Ismail Akhalwaya, Shashanka Ubaru, Kenneth Clarkson et al.