SOTAVerified

Computational Efficiency

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

Papers

Showing 91100 of 4891 papers

TitleStatusHype
Retrieval Augmented Generation Evaluation in the Era of Large Language Models: A Comprehensive SurveyCode2
CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive SurveyCode2
Enhancing Autonomous Driving Systems with On-Board Deployed Large Language ModelsCode2
InteractRank: Personalized Web-Scale Search Pre-Ranking with Cross Interaction FeaturesCode2
RWKVTTS: Yet another TTS based on RWKV-7Code2
Scaling Video-Language Models to 10K Frames via Hierarchical Differential DistillationCode2
Re-thinking Temporal Search for Long-Form Video UnderstandingCode2
LandMarkSystem Technical ReportCode2
SuperFlow++: Enhanced Spatiotemporal Consistency for Cross-Modal Data PretrainingCode2
BitDecoding: Unlocking Tensor Cores for Long-Context LLMs Decoding with Low-Bit KV CacheCode2
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05Unverified