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Found 3 papers, 2 papers with code
Amphista: Bi-directional Multi-head Decoding for Accelerating LLM Inference
On MT-Bench, Amphista delivers up to 2. 75$\times$ speedup over vanilla autoregressive decoding and 1. 40$\times$ over Medusa on Vicuna 33B in wall-clock time.
When Parameter-efficient Tuning Meets General-purpose Vision-language Models
Instruction tuning has shown promising potential for developing general-purpose AI capabilities by using large-scale pre-trained models and boosts growing research to integrate multimodal information for creative applications.
Prototypical Mixing and Retrieval-Based Refinement for Label Noise-Resistant Image Retrieval
This paper investigates a realistic but understudied problem of image retrieval under label noise, which could lead to severe overfitting or memorization of noisy samples during optimization.
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