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Particle-Based Score Estimation for Jointly Learning Transition and Observation Models in Autonomous Driving
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Unbiased and Efficient Sampling of Dependency Trees
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Large-Scale Retrieval for Reinforcement Learning
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Characteristics of Harmful Text: Towards Rigorous Benchmarking of Language Models
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Score-Based Diffusion meets Annealed Importance Sampling
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Learning to Navigate Wikipedia by Taking Random Walks
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Semantic Exploration from Language Abstractions and Pretrained Representations
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A Generalist Agent
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Active Acquisition for Multimodal Temporal Data: A Challenging Decision-Making Task
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What is the simplest model that can account for high-fidelity imitation?
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Diagnosing failures of fairness transfer across distribution shift in real-world medical settings
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Learning to Configure Computer Networks with Neural Algorithmic Reasoning
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Latent Space Smoothing for Individually Fair Representations
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Testing Independence of Exchangeable Random Variables
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Why neural networks find simple solutions: the many regularizers of geometric complexity
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Self-supervised video pretraining yields strong image representations
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Beyond Bayes-optimality: meta-learning what you know you don’t know
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Transformers generalize differently from in-context and in-weights information
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Palm up: Playing in the Latent Manifold for Unsupervised Pretraining
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Game Theoretic Rating in n-player general-sum games with Equilibria
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Optimistic posterior sampling for reinforcement learning with few samples and tight guarantees
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Co-Writing Screenplays and Theatre Scripts with Language Models: An Evaluation by Industry Professionals
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Where Should I Spend My FLOPS? Efficiency Evaluations of Visual Pre-training Methods
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COptiDICE: Offline Constrained Reinforcement Learning via Stationary Distribution Correction Estimation
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Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality