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Showing papers from Tsinghua University, Microsoft Show all papers

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NeurIPS 2026Tsinghua University, TsinghuaTsinghuaTsinghua University, MicrosoftXiaomi CorporationMicrosoft Research AsiaLLM pretraining & scaling laws

Memory Grafting: Scaling Language Model Pre-training via Offline Conditional Memory

Memory Grafting uses frozen hidden states from a grafting model as conditional n-gram memory for language models, improving average benchmarks to 53.86 versus 52.43 for vanilla Engram at 2.8B scale with minimal overhead.

Runxi Cheng, Yuchen Guan, Yongxian Wei, Qianpu Sun and 6 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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lenient 4/5
medium 6/10
strict 0/5
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NeurIPS 2026Tsinghua University, TsinghuaXiaobing.AIPekingAdvanced Micro DevicesTsinghua University, MicrosoftEmbodied agents

TaskGround: Structured Executable Task Inference for Full-Scene Household Reasoning

TaskGround grounds full household scenes into task-relevant slices to infer executable task structures, improving compact open-weight models' success rates by large margins over direct prompting while cutting token costs up to 18x.

ZhiYuan Feng, Yu Deng, Ruichuan An, Zhenhua Liu and 10 more

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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17/20 AI panelreviewers recommend it

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AI panel: 17 of 20 reviewers recommend it
lenient 5/5
medium 9/10
strict 3/5