Can large language models explore in-context?
Paper
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2403.15371
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Published
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30
Papers - University - Carnegie Mellon University
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Long-context LLMs Struggle with Long In-context Learning
Paper • 2404.02060 • Published • 32 -
PIQA: Reasoning about Physical Commonsense in Natural Language
Paper • 1911.11641 • Published • 2 -
AQuA: A Benchmarking Tool for Label Quality Assessment
Paper • 2306.09467 • Published • 1 -
Sigma: Siamese Mamba Network for Multi-Modal Semantic Segmentation
Paper • 2404.04256 • Published • 5 -
OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments
Paper • 2404.07972 • Published • 40 -
Megalodon: Efficient LLM Pretraining and Inference with Unlimited Context Length
Paper • 2404.08801 • Published • 61 -
TriForce: Lossless Acceleration of Long Sequence Generation with Hierarchical Speculative Decoding
Paper • 2404.11912 • Published • 15 -
SpecInfer: Accelerating Generative LLM Serving with Speculative Inference and Token Tree Verification
Paper • 2305.09781 • Published • 3 -
Latent Positional Information is in the Self-Attention Variance of Transformer Language Models Without Positional Embeddings
Paper • 2305.13571 • Published • 2 -
Caduceus: Bi-Directional Equivariant Long-Range DNA Sequence Modeling
Paper • 2403.03234 • Published • 11 -
Stylus: Automatic Adapter Selection for Diffusion Models
Paper • 2404.18928 • Published • 12 -
Are Sixteen Heads Really Better than One?
Paper • 1905.10650 • Published • 2 -
Prometheus 2: An Open Source Language Model Specialized in Evaluating Other Language Models
Paper • 2405.01535 • Published • 71