ICML
Collection
Accepted papers for ICML (International Conference on Machine Learning), one dataset per year. • 13 items • Updated
title stringlengths 15 153 | paper_url stringlengths 42 42 | authors listlengths 1 71 | type stringclasses 3
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values | abstract large_stringlengths 422 2.2k | keywords listlengths 0 0 | TL;DR large_stringclasses 0
values | submission_number int64 2 10.2k | arxiv_id stringlengths 10 10 ⌀ | arxiv_id_source stringclasses 2
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On Discrete Prompt Optimization for Diffusion Models | https://openreview.net/forum?id=Fw4fBE2rqW | [
"Ruochen Wang",
"Ting Liu",
"Cho-Jui Hsieh",
"Boqing Gong"
] | Poster | null | This paper introduces the first gradient-based framework for prompt optimization in text-to-image diffusion models. We formulate prompt engineering as a discrete optimization problem over the language space. Two major challenges arise in efficiently finding a solution to this problem: (1) Enormous Domain Space: Setting... | [] | null | 10,207 | 2407.01606 | title_snapshot | [
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Multi-View Clustering by Inter-cluster Connectivity Guided Reward | https://openreview.net/forum?id=uEx2bSAJu8 | [
"Hao Dai",
"Yang Liu",
"Peng Su",
"Hecheng Cai",
"Shudong Huang",
"Jiancheng Lv"
] | Poster | null | Multi-view clustering has been widely explored for its effectiveness in harmonizing heterogeneity along with consistency in different views of data. Despite the significant progress made by recent works, the performance of most existing methods is heavily reliant on strong priori information regarding the true cluster ... | [] | null | 10,190 | null | null | [
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Overestimation, Overfitting, and Plasticity in Actor-Critic: the Bitter Lesson of Reinforcement Learning | https://openreview.net/forum?id=5vZzmCeTYu | [
"Michal Nauman",
"Michał Bortkiewicz",
"Piotr Miłoś",
"Tomasz Trzcinski",
"Mateusz Ostaszewski",
"Marek Cygan"
] | Poster | null | Recent advancements in off-policy Reinforcement Learning (RL) have significantly improved sample efficiency, primarily due to the incorporation of various forms of regularization that enable more gradient update steps than traditional agents. However, many of these techniques have been tested in limited settings, often... | [] | null | 10,168 | 2403.00514 | title_snapshot | [
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Copyright Traps for Large Language Models | https://openreview.net/forum?id=LDq1JPdc55 | [
"Matthieu Meeus",
"Igor Shilov",
"Manuel Faysse",
"Yves-Alexandre de Montjoye"
] | Poster | null | Questions of fair use of copyright-protected content to train Large Language Models (LLMs) are being actively debated. Document-level inference has been proposed as a new task: inferring from black-box access to the trained model whether a piece of content has been seen during training. SOTA methods however rely on nat... | [] | null | 10,167 | 2402.09363 | title_snapshot | [
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Implicit meta-learning may lead language models to trust more reliable sources | https://openreview.net/forum?id=Fzp1DRzCIN | [
"Dmitrii Krasheninnikov",
"Egor Krasheninnikov",
"Bruno Kacper Mlodozeniec",
"Tegan Maharaj",
"David Krueger"
] | Poster | null | We demonstrate that large language models (LLMs) may learn indicators of document usefulness and modulate their updates accordingly. We introduce random strings ("tags") as indicators of usefulness in a synthetic fine-tuning dataset. Fine-tuning on this dataset leads to **implicit meta-learning (IML)**: in further fine... | [] | null | 10,166 | 2310.15047 | title_snapshot | [
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Dr. Strategy: Model-Based Generalist Agents with Strategic Dreaming | https://openreview.net/forum?id=HsseRq2FAx | [
"Hany Hamed",
"Subin Kim",
"Dongyeong Kim",
"Jaesik Yoon",
"Sungjin Ahn"
] | Poster | null | Model-based reinforcement learning (MBRL) has been a primary approach to ameliorating the sample efficiency issue as well as to make a generalist agent. However, there has not been much effort toward enhancing the strategy of dreaming itself. Therefore, it is a question *whether and how an agent can ``*dream better*''*... | [] | null | 10,161 | 2402.18866 | title_snapshot | [
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When Will Gradient Regularization Be Harmful? | https://openreview.net/forum?id=60vC1FY0dZ | [
"Yang Zhao",
"Hao Zhang",
"Xiuyuan Hu"
] | Poster | null | Gradient regularization (GR), which aims to penalize the gradient norm atop the loss function, has shown promising results in training modern over-parameterized deep neural networks. However, can we trust this powerful technique? This paper reveals that GR can cause performance degeneration in adaptive optimization sce... | [] | null | 10,159 | 2406.09723 | title_snapshot | [
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Efficient Algorithms for Empirical Group Distributionally Robust Optimization and Beyond | https://openreview.net/forum?id=pOJbk4Nzmi | [
"Dingzhi Yu",
"Yunuo Cai",
"Wei Jiang",
"Lijun Zhang"
] | Poster | null | In this paper, we investigate the empirical counterpart of Group Distributionally Robust Optimization (GDRO), which aims to minimize the maximal empirical risk across $m$ distinct groups. We formulate empirical GDRO as a *two-level* finite-sum convex-concave minimax optimization problem and develop an algorithm called ... | [] | null | 10,129 | 2403.03562 | title_snapshot | [
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Evaluation of Trajectory Distribution Predictions with Energy Score | https://openreview.net/forum?id=FCmWhJQ14I | [
"Novin Shahroudi",
"Mihkel Lepson",
"Meelis Kull"
] | Poster | null | Predicting the future trajectory of surrounding objects is inherently uncertain and vital in the safe and reliable planning of autonomous systems such as in self-driving cars. Although trajectory prediction models have become increasingly sophisticated in dealing with the complexities of spatiotemporal data, the evalua... | [] | null | 10,124 | null | null | [
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Causal Discovery with Fewer Conditional Independence Tests | https://openreview.net/forum?id=HpT19AKddu | [
"Kirankumar Shiragur",
"Jiaqi Zhang",
"Caroline Uhler"
] | Poster | null | Many questions in science center around the fundamental problem of understanding causal relationships. However, most constraint-based causal discovery algorithms, including the well-celebrated PC algorithm, often incur an _exponential_ number of conditional independence (CI) tests, posing limitations in various applica... | [] | null | 10,108 | 2406.01823 | title_snapshot | [
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Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion | https://openreview.net/forum?id=hZ0fWhgVch | [
"Xuantong LIU",
"Tianyang Hu",
"Wenjia Wang",
"Kenji Kawaguchi",
"Yuan Yao"
] | Poster | null | As a dominant force in text-to-image generation tasks, Diffusion Probabilistic Models (DPMs) face a critical challenge in controllability, struggling to adhere strictly to complex, multi-faceted instructions. In this work, we aim to address this alignment challenge for conditional generation tasks. First, we provide an... | [] | null | 10,107 | 2402.16305 | title_snapshot | [
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