Papers by Shuyan Yang
SUPERB-SG: Enhanced Speech processing Universal PERformance Benchmark for Semantic and Generative Capabilities (2022.acl-long)
Copied to clipboard
Hsiang-Sheng Tsai, Heng-Jui Chang, Wen-Chin Huang, Zili Huang, Kushal Lakhotia, Shu-wen Yang, Shuyan Dong, Andy Liu, Cheng-I Lai, Jiatong Shi, Xuankai Chang, Phil Hall, Hsuan-Jui Chen, Shang-Wen Li, Shinji Watanabe, Abdelrahman Mohamed, Hung-yi Lee
| Challenge: | Existing evaluation methods for transfer learning are limited in speech research . authors show that pre-trained models transfer well across multiple tasks . |
| Approach: | They propose a benchmark to evaluate pre-trained models by increasing task diversity and difficulty over SUPERB. |
| Outcome: | The proposed benchmark increases task diversity and difficulty over SUPERB-SG. |
Self-Awareness before Action: Mitigating Logical Inertia via Proactive Cognitive Awareness (2026.findings-acl)
Copied to clipboard
| Challenge: | Existing work on abductive and long-context reasoning reports that current models still lack self-awareness of missing premises. |
| Approach: | They propose a reasoning framework that introduces self-awareness of missing premises before making the final decision. |
| Outcome: | SABA achieves best performance on all three difficulty splits of detective puzzle benchmark . a small early mistake can remain uncorrected and can guide later reasoning . |
Causal Reasoning of Entities and Events in Procedural Texts (2023.findings-eacl)
Copied to clipboard
| Challenge: | Existing work on entity state tracking or event reasoning is limited to procedural texts. |
| Approach: | They propose a benchmark for causal reasoning of event plausibility and entity states . they represent entities as programming languages while prompting language models . |
| Outcome: | The proposed model outperforms existing models on human reasoning and event reasoning. |
Show Me More Details: Discovering Hierarchies of Procedures from Semi-structured Web Data (2022.acl-long)
Copied to clipboard
| Challenge: | Existing work has treated procedures as shallow structures without modeling the parent-child relation. |
| Approach: | They propose to construct an open-domain hierarchical knowledge-base (KB) of procedures based on wikiHow . they link steps in an article to other articles with similar goals, recursively building the KB . |
| Outcome: | The proposed method significantly outperforms baselines according to automatic evaluation, human judgment, and application to downstream tasks such as instructional video retrieval. |
Optimizing NLU Reranking Using Entity Resolution Signals in Multi-domain Dialog Systems (2021.naacl-industry)
Copied to clipboard
Tong Wang, Jiangning Chen, Mohsen Malmir, Shuyan Dong, Xin He, Han Wang, Chengwei Su, Yue Liu, Yang Liu
| Challenge: | In dialog systems, the Natural Language Understanding component makes the interpretation decision before the mentioned entities are resolved. |
| Approach: | They propose to leverage Entity Resolution (ER) features in NLU reranking to learn model weights . they propose a score distribution matching method to ensure the models are calibrated . |
| Outcome: | The proposed approach outperforms the baseline model on multiple domain evaluations. |
Language Models of Code are Few-Shot Commonsense Learners (2022.emnlp-main)
Copied to clipboard
| Challenge: | Existing approaches to generate graphs using pre-trained language models hinder their ability to generate them correctly. |
| Approach: | They propose to frame structured commonsense reasoning tasks as code generation tasks instead of serializing the output graph as a flat list of nodes and edges. |
| Outcome: | The proposed approach outperforms natural-language LMs in three natural language tasks even when the downstream task does not involve source code at all. |