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论文精选 83arXiv

When to Assist and What to Suggest: Joint Gating and Memory-Grounded Hint Generation in One Compact Decoder· 何时辅助与建议:紧凑解码器中的联合门控和基于记忆的提示生成

Proactive assistants offer short, memory-grounded hints during a conversation, deciding when to assist and what to suggest. Current systems split this between a gate and a larger generator; we evaluate both together on 28,058 decision points. Stage-wise generation scores are oracle-gate ceilings: behind a real gate, end-to-end exact match is 0.2619 against a ceiling of 0.2971, and end-to-end precision is 0.2387, leaving substantial headroom. A gate pays off through precision and compute, whose saving falls from 4.39x with an 8B generator to 1.38x with a 1B one. The memory profile drives hint quality: removing it costs 24.7 exact-match points (rescaled BERTScore 0.57 to 0.35), while retrieval and a larger generator add nothing on exact match. One 1B decoder can do both, gating from an inter

领域:cs.CL作者:A. J. A. Jubayer Talukder、Mohammad Ariful Haque
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论文精选 82

Elucidating the Design Space of LM Data Attribution· 阐明大模型数据归属的设计空间

Data attribution methods for Language Models (LMs) are typically evaluated using downstrea…

领域:cs.CL作者:Steven Yu、Sheng-Yu Wang、Kimia Hamidieh
📎 arXiv🕒 10-30 01:59🔗 arxiv.org

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