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Feng Tian

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#artificial intelligence Preprint Oct 2026

Trace Evolution Bench: Measuring Whether Agents Improve from Their Own Environment Traces

Self-evolving agents are usually scored by endpoint Gain: held-out success after an update minus success before. That difference can credit a frozen rescore as evolution. We introduce Trace Evolution Bench (TEB), a protocol that separates that rescore from a context or weight update, together with three frozen 80/20/40...

Fang-Fei Li, Chen-Yang Zhao, Long Wang et al. · 0 citations
#artificial intelligence Preprint Sep 2026

xDailyBench: Benchmarking LLMs on Professional Consultation for Real-Life Problems

Large language models (LLMs) are increasingly used for everyday assistance, yet existing benchmarks only partially reflect the requests users naturally make in practice. Real-world requests are often open-ended, casually specified, and context-dependent, requiring models not only to follow explicit instructions but als...

Yong Peng, Qing-Shui Gu, Li-Ya Zhu et al. · 0 citations
#natural language process... Preprint Jul 2026

ZenGen: Social Mind for LLMs

ZenGen, an integrated framework for measuring, internalizing, and grounding social intelligence, and Actio, a harness-controlled inference architecture that routes four typed supports into reasoning demonstrate the effectiveness of typed runtime support.

ZenGen Team, Xiang Ao, Jingping Bi et al. · 0 citations
Book Open access Aug 2026

Connecting 100K+ GPUs: Building the Communication Stack for Large-Scale LLM Training

This work presents Meta's network architecture and software stack designed to support one of the world's largest RoCE fabrics, currently connecting over 100,000 GPUs across multiple datacenter buildings, and introduces a scalable initialization strategy that reduces startup times by 11× via eager process group creation...

Hongyi Zeng, Min Si, Pavan Balaji et al. · 0 citations

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