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  1. Home
  2. Signal Canvas
  3. HeRo-Q: A General Framework for Stable Low Bit Quantization
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HeRo-Q: A General Framework for Stable Low Bit Quantization via Hessian Conditioning

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Viability
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Evidence Receipt

Freshness: 2026-04-02T02:30:40.136932+00:00

Claims: 0

References: 20

Proof: pending

Distribution: unknown

Source paper: HeRo-Q: A General Framework for Stable Low Bit Quantization via Hessian Conditioning

PDF: https://arxiv.org/pdf/2601.21626v1

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Distribution channel: unknown

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Dimensions overall score 5.0

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Dissecting Quantization Error: A Concentration-Alignment Perspective
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GlowQ: Group-Shared LOw-Rank Approximation for Quantized LLMs
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Score 6.0up
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Preserve-Then-Quantize: Balancing Rank Budgets for Quantization Error Reconstruction in LLMs
Score 6.0up
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SliderQuant: Accurate Post-Training Quantization for LLMs
Score 7.0up
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Breaking the Blocks: Continuous Low-Rank Decomposed Scaling for Unified LLM Quantization and Adaptation
Score 8.0up
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ITQ3_S: High-Fidelity 3-bit LLM Inference via Interleaved Ternary Quantization with Rotation-Domain Smoothing
Score 7.0up
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RAMP: Reinforcement Adaptive Mixed Precision Quantization for Efficient On Device LLM Inference
Score 6.0up

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