Yang Zhao
Yang Zhao has 4 papers in our library, in 2025–2026, most of them on Machine translation, Language models & pretraining, Speech & spoken language; often with Bibo Cai, Bing Qin, Li Du.
OpenAlex · h-index 0 · 3 works · 0 citations OpenAlex, 2026-10-14
📄 4 works in our library · 🔗 Cited 11 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #9739
Affiliations
Fields, topics and concepts
📚 Shelves 8The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 3 worksComputer Science · 3 worksArts and Humanities · 3 worksLanguage and Linguistics · 3 worksCognitive Neuroscience · 1 workNeuroscience · 1 workSafety Research · 1 workSocial Sciences · 1 work
🧭 Topics 5Research subjects and languages the work is about.Evaluation & benchmarks · 1 workMachine translation · 1 workSpeech & spoken language · 1 workVision & language · 1 workLanguage models & pretraining · 1 work
Works by year
2020s
Papers
- TriFine: A Large-Scale Dataset of Vision-Audio-Subtitle for Tri-Modal Machine Translation and Benchmark with Fine-Grained Annotated Tags (2025 · 9 citations)
Video-guided machine translation (VMT) usually feeds a model dense visual features from many frames. This approach is slow, carries a lot of irrelevant signal, and ignores the soundtrack. The authors argue that compact, targeted cues from both vision and audio work better. To test this, they release TriFine, an… - Decoding the Multimodal Mind: Generalizable Brain-to-Text Translation via Multimodal Alignment and Adaptive Routing (2026 · 1 citation)
Most brain-to-text decoders map neural recordings onto a single representation type, such as image or text embeddings. This ignores the fact that perception is cross-modal: reading about a barking dog can also evoke sights and sounds. Ye et al. build a unified decoder on Qwen2.5-Omni that addresses this gap. - MAESTRO: Meta-learning Adaptive Estimation of Scalarization Trade-offs for Reward Optimization (2026 · 1 citation)
GRPO aligns LLMs well when answers can be checked automatically, as in math or code. Open-ended generation has no such check, and its goals often conflict, for example creativity versus factuality. Existing fixes either rely on costly LLM judges or combine cheap heuristic rewards (perplexity, entropy, format) using… - Large Language Models Are Still Misled by Simple Bias Ensembles (2026)
Recent LLMs handle individual shortcut cues better than before. This paper argues that the real weakness appears when several such cues occur together in one input, which is common in real-world text. Most existing bias benchmarks inject only one bias per sample, and a few inject two. The authors therefore built…
All works
- TriFine: A Large-Scale Dataset of Vision-Audio-Subtitle for Tri-Modal Machine Translation and Benchmark with Fine-Grained Annotated TagsInternational Conference on Computational Linguistics (COLING)Boyu Guan, Yining Zhang, Yang Zhao, et al.2025 · 9 citations
- Decoding the Multimodal Mind: Generalizable Brain-to-Text Translation via Multimodal Alignment and Adaptive RoutingFindings of the Association for Computational LinguisticsChunyu Ye, Yunhao Zhang, Jingyuan Sun, et al.2026 · 1 citation
- MAESTRO: Meta-learning Adaptive Estimation of Scalarization Trade-offs for Reward OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Yang Zhao, Hepeng Wang, Xiao Ding, et al.2026 · 1 citation
- Large Language Models Are Still Misled by Simple Bias EnsemblesFindings of the Association for Computational LinguisticsZhouhao Sun, Zhiyuan Kan, Xiao Ding, et al.2026
- Consolidation or Adaptation? PRISM: Disentangling SFT and RL Data via Gradient Concentration ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetYang Zhao et al.2026
Co-authors here
- Bibo Cai ×2
- Bing Qin ×2
- Li Du ×2
- Ting Liu ×2
- Xiao Ding ×2
- Zhouhao Sun ×2
- Chengqing Zong
- Chong Li
- Kai Xiong
- Shaonan Wang
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL) ×2: ACL 2026
- Findings of the Association for Computational Linguistics ×2: Findings of the Association for Computational Linguistics 2026 ×2
- International Conference on Computational Linguistics (COLING): COLING 2025
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