Chenglong Wang

Chenglong Wang has 3 papers in our library, in 2026, most of them on Language models & pretraining; often with Jingbo Zhu, Tong Xiao, Qiaozhi He.

3 papers in our library · 2026

The profile is the library's match of the name; two people with one name are not always told apart.

Affiliations

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

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

The most cited first (OpenAlex and our library).

Cross-layer Attention Sharing for Pre-trained Large Language Models (2026 · 2 citations)
Earlier work on making LLM attention more efficient mostly targets redundancy inside a layer, for example by compressing the KV cache or grouping heads.
RouteLMT: Learned Sample Routing for Hybrid LLM Translation Deployment (2026)
Serving every translation request with a large LLM is too costly for industrial systems. Hybrid setups therefore send most traffic to a small model and escalate only some inputs to a large one. The authors treat this escalation decision as spending a fixed budget of large-model calls. They argue that requests should…
SERM: Self-Evolving Relevance Model with Agent-Driven Learning from Massive Query Streams (2026)
Search relevance models trained on fixed datasets lose accuracy as live query traffic changes, for example when users adopt new slang or cultural references.

12 of 15 co-authors with a page, the most papers together first.

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

Papers of our library cite their works 1 time (of the 149,439 papers whose bibliographies we read).

Updated 1 November 2026