CAQ-ZO aligns ZO query stencils to compander grids, eliminating query-time residual error and improving NF4 fine-tuning performance on Qwen and Llama models compared to standard quantized baselines.
Gray and David L
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
SeCo performs semantic-driven context compression for LLMs by anchoring on query-relevant semantic centers and applying consistency-weighted token merging, yielding better downstream performance, lower latency, and stronger out-of-domain robustness than position-based methods across 14 benchmarks.
citing papers explorer
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Compander-Aligned Query Geometry for Quantized Zeroth-Order Optimization
CAQ-ZO aligns ZO query stencils to compander grids, eliminating query-time residual error and improving NF4 fine-tuning performance on Qwen and Llama models compared to standard quantized baselines.
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Beyond Position Bias: Shifting Context Compression from Position-Driven to Semantic-Driven
SeCo performs semantic-driven context compression for LLMs by anchoring on query-relevant semantic centers and applying consistency-weighted token merging, yielding better downstream performance, lower latency, and stronger out-of-domain robustness than position-based methods across 14 benchmarks.