🧑‍🔬 Shaoning Zeng

🏛️ Affiliations

🎓University of Electronic Science and Technology of ChinaChengdu · China2021–2026 · 51 paperscurrent🎓Zhejiang International Studies UniversityHangzhou · China2026 · 1 papercurrent🎓Huizhou UniversityHuizhou · China2016–2021 · 25 papers🎓University of MacauMacao · China2017–2021 · 13 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. H-MEM: Hierarchical Memory for High-Efficiency Long-Term Reasoning in LLM Agents (2026 · 8 citations)
   LLM agents in long conversations must draw on past interactions, but common memory designs fall short. Flat vector stores such as MemoryBank compare each query against every stored entry, so cost grows quickly as memory accumulates, and graph-style memories are hard to keep consistent. H-MEM addresses this by…
2. Preference-Aware Memory Update for Long-Term LLM Agents (2026 · 4 citations)
   Long-running LLM agents usually rely on memory systems such as MemoryBank, MemGPT, MemInsight or A-MEM. These systems mostly improve how memory is stored and retrieved. They pay little attention to keeping memory current as a user's preferences change over time. The authors propose PAMU (Preference-Aware Memory…
3. A Dual-Phase Self-Evolution Framework for Large Language Models (2026)
   Post-training methods such as preference optimization or memory-augmented prompting help LLMs match user expectations, but they leave the model's underlying domain knowledge mostly unchanged.
4. Think Parallax: Solving Multi-Hop Problems via Multi-View Knowledge-Graph-Based Retrieval-Augmented Generation (2026)
   Knowledge-graph-based RAG (KG-RAG) systems often fail on multi-hop questions. They encode the question and all graph triples into one shared vector space, which blends together the semantics that each reasoning step needs. The authors observe that Transformer attention heads tend to take on different relations at…

🤝 Co-authors here

2 co-authors with a page, the most papers together first.

• Haoran Sun ×3
• Zekun Zhang ×2

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Findings of the Association for Computational Linguistics ×2: Findings of the Association for Computational Linguistics 2026 ×2
• Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2026
• Conference of the European Chapter of the Association for Computational Linguistics (EACL): EACL 2026

🔗 Cited by

Papers of our library cite their works 7 times (of the 149,439 papers whose bibliographies we read); 3 citing papers with a page here →.

Updated 1 November 2026

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