Shengyi Liao

Shengyi Liao has 3 papers in our library, in 2024–2025, most of them on Reasoning, Question answering; often with Chenliang Li, Fei Huang, Weizhou Shen.

3 papers in our library · 2024–2025

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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).

Leave No Document Behind: Benchmarking Long-Context LLMs with Extended Multi-Doc QA (2024 · 72 citations)
Most current long-context benchmarks make inputs longer by padding them with unrelated filler text. In those setups, the evidence for an answer usually sits in one place, so a model can skip most of the input and still answer correctly. Wang et al. address this with Loong, a multi-document QA benchmark where every…
QwenLong-L1: Towards Long-Context Large Reasoning Models with Reinforcement Learning (2025 · 13 citations)
Reinforcement learning has made large reasoning models (LRMs) much better at problems with short inputs. It is still unclear how to train them to reason over very long documents, potentially around 120K tokens. The authors frame this as "long-context reasoning RL," where the model must first find and ground the…
QwenLong-L1.5: Post-Training Recipe for Long-Context Reasoning and Memory Management (2025 · 10 citations)
Research on long contexts has mostly targeted pre-training and architecture, so post-training lags behind.

12 of 22 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 81 times (of the 149,439 papers whose bibliographies we read); 19 citing papers with a page here →.

Updated 30 October 2026