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#02 research signal
quantization / compression

BitsMoE: Spectral Energy-Guided Bit Allocation for MoE LLM Quantization (+27.83pp over GPTQ at 2-bit)

1 min read updated 1w ago 16 prior views

SVD-based mixed-precision quantization framework for MoE models: separates shared basis from expert-specific factors, allocates bits via integer linear programming. +27.83pp accuracy over GPTQ under 2-bit Qwen3-30B-A3B, 12.3x decoding acceleration. Code public.

what changed today research note high confidence
arxiv.org ↗
#03 research signal
agent-protocols / reasoning / inference

Emergent Collaborative Deliberation Protocol: BFT-Derivative Multi-Model Synthesis

1 min read updated 1w ago 20 prior views

Byzantine Fault Tolerance-derived multi-agent deliberation protocol assigns engineered cognitive personas to language models, separating model capability from reasoning style. Across 1478 sessions: free edge-inference models at $0.0002/batch match frontier models at $10,690/batch in analytical output.

what changed today research note high confidence
arxiv.org ↗
#05 research signal
research / multimodal / computer-vision

Mitigating Perceptual Judgment Bias in Multimodal LLM-as-a-Judge via Perceptual Perturbation and Reward Modeling

1 min read updated 1w ago editorial rank #05

Recent multimodal large language models have demonstrated strong reasoning ability, yet their reliability as automated evaluators remains limited by a critical weakness: when visual evidence conflicts with textual cues,

what changed today research note high confidence
arxiv.org ↗
#06 research signal
research / multimodal / reasoning

ProtoAda: Prototype-Guided Adaptive Adapter Expansion and Geometric Consolidation for Multimodal Continual Instruction Tuning

1 min read updated 1w ago editorial rank #06

Multimodal Large Language Models (MLLMs) achieve strong performance through instruction tuning, but real-world deployment requires them to continually acquire new vision-language capabilities, making Multimodal Continual

what changed today research note high confidence
arxiv.org ↗