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Measuring Large Language Models Capacity to Annotate Journalistic Sourcing
Measuring Large Language Models Capacity to Annotate Journalistic Sourcing
Arxiv
0+阅读 · 4月3日
Mixture of Attentions For Speculative Decoding
Mixture of Attentions For Speculative Decoding
Arxiv
0+阅读 · 4月3日
On Vanishing Variance in Transformer Length Generalization
On Vanishing Variance in Transformer Length Generalization
Arxiv
0+阅读 · 4月3日
A Framework for Situating Innovations, Opportunities, and Challenges in Advancing Vertical Systems with Large AI Models
A Framework for Situating Innovations, Opportunities, and Challenges in Advancing Vertical Systems with Large AI Models
Arxiv
0+阅读 · 4月3日
Reducing Reasoning Costs: The Path of Optimization for Chain of Thought via Sparse Attention Mechanism
Reducing Reasoning Costs: The Path of Optimization for Chain of Thought via Sparse Attention Mechanism
Arxiv
0+阅读 · 4月3日
On Model Protection in Federated Learning against Eavesdropping Attacks
On Model Protection in Federated Learning against Eavesdropping Attacks
Arxiv
0+阅读 · 4月2日
FT-Transformer: Resilient and Reliable Transformer with End-to-End Fault Tolerant Attention
Arxiv
0+阅读 · 4月3日
MegaScale-Infer: Serving Mixture-of-Experts at Scale with Disaggregated Expert Parallelism
Arxiv
0+阅读 · 4月3日
Challenges and Trends in Egocentric Vision: A Survey
Arxiv
0+阅读 · 4月3日
Niche Dynamics in Complex Online Community Ecosystems
Niche Dynamics in Complex Online Community Ecosystems
Arxiv
0+阅读 · 4月2日
Group-based Distinctive Image Captioning with Memory Difference Encoding and Attention
Group-based Distinctive Image Captioning with Memory Difference Encoding and Attention
Arxiv
0+阅读 · 4月3日
Beyond the Spell: A Dynamic Logic Analysis of Misdirection
Arxiv
0+阅读 · 4月3日
Learning Audio-guided Video Representation with Gated Attention for Video-Text Retrieval
Arxiv
0+阅读 · 4月3日
LakeVisage: Towards Scalable, Flexible and Interactive Visualization Recommendation for Data Discovery over Data Lakes
LakeVisage: Towards Scalable, Flexible and Interactive Visualization Recommendation for Data Discovery over Data Lakes
Arxiv
0+阅读 · 4月2日
Why do LLMs attend to the first token?
Arxiv
0+阅读 · 4月3日
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