Papers by Junhong Liang
ServImage: An Image Generation and Editing Benchmark from Real-world Commercial Imaging Services (2026.acl-long)
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Fengxian Ji, Jingpu Yang, Zirui Song, Lang Gao, Junhong Liang, Zhenhao Chen, Jinghui Zhang, Xiuying Chen
| Challenge: | Recent image generation and editing models demonstrate robust adherence to instructions and high visual quality on academic benchmarks. |
| Approach: | They propose a benchmark that correlates image outputs with economic value in commercial design projects. |
| Outcome: | ServImage benchmarks show image generation models perform well on academic benchmarks but are uncertain on commercial projects. |
Improve Interpretability of Neural Networks via Sparse Contrastive Coding (2022.findings-emnlp)
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| Challenge: | XAI has achieved remarkable advances, but few efforts have been devoted to solving the problem. |
| Approach: | They propose a model-agnostic explanation method termed Sparse Contrastive Coding . they use model-based explanations to explain the black-box in a more model-oriented way . |
| Outcome: | The proposed method outperforms five state-of-the-art methods in interpretability and classification metrics. |
CLAMBER: A Benchmark of Identifying and Clarifying Ambiguous Information Needs in Large Language Models (2024.acl-long)
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Tong Zhang, Peixin Qin, Yang Deng, Chen Huang, Wenqiang Lei, Junhong Liu, Dingnan Jin, Hongru Liang, Tat-Seng Chua
| Challenge: | Large language models are used to meet user information needs, but their effectiveness in dealing with user queries that contain various types of ambiguity remains unknown. |
| Approach: | They propose a benchmark for evaluating large language models using a well-organized taxonomy. |
| Outcome: | The proposed model is based on a well-organized taxonomy and compares it with other models. |
Towards Effective Automatic Debt Collection with Persona Awareness (2023.emnlp-industry)
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| Challenge: | Existing debt collection agents fail to tailor strategies to debtor personas, leading to ineffective collection. |
| Approach: | They present a commercial practice on debt collection agents that organizes debtor personas into a taxonomy and constructs a persona-aware conversation dataset. |
| Outcome: | The proposed agent increases recovery rate by 3.31% and collects additional 100K RMB after two months of testing. |
Cultural Benchmarking of LLMs in Standard and Dialectal Arabic Dialogues (2026.acl-long)
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Muhammad Dehan Al Kautsar, Saeed Almheiri, Momina Ahsan, Bilal Elbouardi, Younes Samih, Sarfraz Ahmad, Amr Keleg, Omar El Herraoui, Kareem Elzeky, Abed Alhakim Freihat, Mohamed Anwar, Zhuohan Xie, Junhong Liang, Mohammad Rustom Al Nasar, Preslav Nakov, Fajri Koto
| Challenge: | Most benchmarks focus on short text snippets in Modern Standard Arabic (MSA), overlooking cultural nuances that naturally arise in dialogues. |
| Approach: | They propose a culturally grounded conversational dataset covering 13 Arabic-speaking countries, in both Modern Standard Arabic (MSA) and each country’s respective dialect, spanning 12 daily-life topics and 54 fine-grained subtopics. |
| Outcome: | The proposed model performs worse on all three tasks than the MSA benchmark. |