co-evolution 1context compression 1kv cache 1large language models 1long-context inference 1memory selection 1model efficiency 1rubric generation 1solver improvement 1text-space optimization 1
From the 2 of 7 linked papers with an AI index.
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cs.AI2026
Quantization Degradation in Large Language Models: A Signal-Noise Perspective
Chenxi Zhou, Pengfei Cao, Jinyu Ye +5
Post-training quantization reduces the deployment cost of large language models, yet how severely a quantized model degrades is not determined by bit-width alone. We systematically…
cs.AI2026
DecoEvo: Score-Decoupled Co-Evolution of Solver and Rubric-Generator Skills in Text Space
Jiangwang Chen, Zixin Song, Junlin Liu +10
The paper introduces DecoEvo, a method that co-evolves a solver and a rubric-generator for large language models in text space using decoupled objectives, allowing the solver to im…
cs.AI2026
From Proprietary to Open-Source: Bridging the Distribution Gap via Multi-Agent Protocol Distillation in Agentic Search
Junlin Liu, Jiangwang Chen, Zixin Song +7
Agentic search enables large language models to solve knowledge-intensive tasks by interleaving multi-step reasoning with retrieval, yet optimizing this with outcome-based reinforc…