Qiang Zhang
Qiang Zhang has 5 papers in our library, in 2022–2026, most of them on Language models & pretraining, Dialogue systems, Evaluation & benchmarks; often with Aldo Lipani, Eli Shechtman, Emine Yilmaz.
OpenAlex · ORCID · h-index 28 · 125 works · 2,632 citations OpenAlex, 2026-10-14
📄 5 works in our library · 🔗 Cited 190 times in our library · ⭐ Paper Stars ranking: #5686
Affiliations
Fields, topics and concepts
📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Computer Science · 5 worksComputer Vision and Pattern Recognition · 3 worksArts and Humanities · 4 worksArtificial Intelligence · 4 worksLanguage and Linguistics · 4 works
🧭 Topics 4Research subjects and languages the work is about.Language models & pretraining · 2 worksDialogue systems · 1 workEvaluation & benchmarks · 1 workReasoning · 1 work
Works by year
2020s
Papers
- From Slow Bidirectional to Fast Autoregressive Video Diffusion Models (2024 · 148 citations)
Most strong text-to-video diffusion models use bidirectional attention across all frames. As a result, no frame can be shown until the whole clip is denoised, and cost grows quadratically with length. This rules out streaming or interactive use. The authors present CausVid, which converts a pretrained bidirectional… - StepGame: A New Benchmark for Robust Multi-Hop Spatial Reasoning in Texts (2022 · 71 citations)
The paper argues that near-perfect scores on the spatial tasks of bAbI (tasks 17 and 19) overstate what models can do, because bAbI uses a handful of fixed phrasings, needs only one or two reasoning steps, and most test pairs also occur in training. - SciKnowEval: Evaluating Multi-level Scientific Knowledge of Large Language Models (2024 · 36 citations)
SciKnowEval is a benchmark for measuring how much scientific knowledge large language models hold and how well they use it. - A Survey on Asking Clarification Questions Datasets in Conversational Systems (2023 · 28 citations)
Research on asking clarification questions (ACQs) in conversational systems is hard to compare across studies. - TARo: Token-level Adaptive Routing for LLM Test-time Alignment (2026)
Test-time alignment steers a frozen LLM during decoding with a smaller reward model, avoiding expensive post-training such as RLVR.
Co-authors here
- Aldo Lipani ×2
- Eli Shechtman
- Emine Yilmaz
- Hanqing Zeng
- Kehua Feng
- Keyan Ding
- Weijie Wang
- Xi Wang
- Xun Huang
- Yue Feng
- Yunkai Zhang
- Yuqi Tang
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2023
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
- IEEE Computer Society Conference on Computer Vision and Pattern Recognition: IEEE Computer Society Conference on Computer Vision and Pattern Recognition 2024
- Proceedings of the AAAI Conference on Artificial Intelligence: Proceedings of the AAAI Conference on Artificial Intelligence 2022
Cited by
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