Chinese University of Hong Kong

Headlines · 3

1. Oct 20
   HKUST-led team's HeLa-Mem links distant memories for AI agents

   Researchers from HKUST (Guangzhou), Jilin University and the Chinese University of Hong Kong have proposed HeLa-Mem (Hebbian Learning Associative Memory), which targets the gap where an AI agent's relevant memories share little wording, and the paper was accepted to ACL 2026 Main with code published on GitHub. Each dialogue turn becomes an episodic memory node; links between nodes strengthen when they are retrieved together and decay when unused, while a reflection agent distils reusable semantic memory from densely connected nodes and flags isolated, stale nodes as forgetting candidates. Retrieval runs both a similarity/keyword/time path and an association-spreading path, merging results with semantic memory for the LLM; on LoCoMo with GPT-4o-mini, the authors report F1 of 40.14 (multi-hop), 47.29 (temporal), 29.70 (open-domain) and 51.89 (single-hop), using about 1010 retrieval-context tokens on average, versus roughly 2000 cited for MemoryOS and about 16910 for full-dialogue input. The authors note association weights must accumulate through interaction, leaving a cold-start challenge when history is thin, and that the distilled knowledge depends on the base LLM's capability.

   36氪 人工智能 · 🔥 0
2. Oct 13
   PAIR 2026 panel weighs what AI can do for quantum computing, and vice versa

   At PAIR Conference 2026 in Shanghai on September 20–21, a roundtable examined how AI can aid quantum R&D and what quantum computing might offer AI. Hu Hongye said the Institute of Physics and the Beijing Academy of Quantum Information Sciences achieved automated calibration at more than 100 qubits without continuous experimenter involvement earlier this year, and that AI is being explored for quantum compilation, verification and error-correction optimization; he noted a Google AI control study required about 10^5–10^6 reinforcement-learning samples. Yan Zheng said strongly correlated many-body problems still need quantum computing advances, Wu Anbang expected AI agents to speed quantum software R&D in two to three years, and Hu's team proved a polynomial memory advantage for quantum generative models in specific tasks.

   MIT科技评论中文 · 🔥 0
3. Oct 12
   Yau leads math-and-AI lab alliance at Tsinghua with 1,000 researchers

   On October 11 the Yau Mathematical Sciences and AI Laboratory Alliance was launched at Tsinghua University, led by Fields Medalist Shing-Tung Yau and formed by eight institutions including Tsinghua's Qiuzhen College, the Yau Mathematical Sciences Center, the Beijing Yanqi Lake Institute of Applied Mathematics, the Morningside Center of Mathematics and the Chinese University of Hong Kong's Zhen-Cross Mathematical Sciences Academy, aiming to bring together roughly 1,000 mathematicians and researchers. The alliance will work on math-specific large models, AI-assisted formal proofs and conjecture discovery, and interpretable AI, with labs planned in Beijing, Shanghai, Nanjing, Shenzhen and Hong Kong that share model-training resources, formal math libraries and compute platforms, plus a planned AI-assisted mathematics journal. Yau described AI's impact as a 'tsunami' that researchers should ride rather than avoid, and said China's own large models are still not world-leading in frontier mathematics and basic science.

   虎嗅 AI · 🔥 0

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