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Shadow Traffic Is the Only Honest Free Model Evaluation

The demo replay played in the dim glow of a conference room, and everyone agreed the free model sounded good. The same four prompts produced crisp summaries, polite error handling, and no obvious…

  • Shadow traffic approach compares free model with primary model
  • Real production traffic used to test free model's performance
  • Metrics like error rates, latency, token consumption analyzed

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QUASAR: How Saliency-Weighted Reconstruction Closes the Loss Floor Gap in LLM Quantization-Aware Training

QUASAR: How Saliency-Weighted Reconstruction Closes the Loss Floor Gap in LLM Quantization-Aware Training Quantization is one of the most practical tools in the LLM deployment toolkit.

  • QUASAR addresses loss floor gap in 2-bit/3-bit quantization of LLMs
  • Saliency-weighted reconstruction prioritizes accurate parameter reconstruction
  • QUASAR achieves up to 29% reduction in KL divergence at 2-bit quantization
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