Papers by James Song
Text-Free Image-to-Speech Synthesis Using Learned Segmental Units (2021.acl-long)
Copied to clipboard
| Challenge: | Existing models for synthesising fluent, natural-sounding spoken audio captions do not require natural language text as an intermediate representation or source of supervision. |
| Approach: | They propose a model for directly synthesizing fluent, natural-sounding spoken audio captions for images that does not require natural language text as an intermediate representation or source of supervision. |
| Outcome: | The proposed model captures diverse visual semantics of images and can replace text with a set of discrete, sub-word speech units. |
Re3val: Reinforced and Reranked Generative Retrieval (2024.findings-eacl)
Copied to clipboard
| Challenge: | generative retrieval models encode pointers to information in a corpus as an index within the model’s parameters. |
| Approach: | They propose a generative retrieval model that leverages contextual information to rerank retrieved page titles and utilizes REINFORCE to maximize rewards generated by constrained decoding. |
| Outcome: | The proposed model can't be tuned for the downstream readers as decoding the page title is a non-differentiable operation. |
When "Correct" Is Not Safe: Can We Trust Functionally Correct Patches Generated by Code Agents? (2026.acl-long)
Copied to clipboard
Yibo Peng, James Song, Lei Li, Xinyu Yang, Mihai Christodorescu, Ravi Mangal, Corina S. Pasareanu, Haizhong Zheng, Beidi Chen
| Challenge: | Code agents are increasingly trusted to autonomously fix bugs on platforms such as GitHub, yet their security evaluation focuses on functional correctness. |
| Approach: | They propose to attack functionally correct yet vulnerable (FCV) patches by combining multi-turn reasoning with tool invocation and environment interaction. |
| Outcome: | The proposed FCV-Attack achieves an attack success rate of 40.7% on GPT-5 Mini + OpenHands. |
COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation (2021.naacl-demos)
Copied to clipboard
Qingyun Wang, Manling Li, Xuan Wang, Nikolaus Parulian, Guangxing Han, Jiawei Ma, Jingxuan Tu, Ying Lin, Ranran Haoran Zhang, Weili Liu, Aabhas Chauhan, Yingjun Guan, Bangzheng Li, Ruisong Li, Xiangchen Song, Yi Fung, Heng Ji, Jiawei Han, Shih-Fu Chang, James Pustejovsky, Jasmine Rah, David Liem, Ahmed ELsayed, Martha Palmer, Clare Voss, Cynthia Schneider, Boyan Onyshkevych
| Challenge: | a new framework to digest relevant biomedical knowledge is needed to combat COVID-19 . quantity of research results is a bottleneck, and false information promoted in publications . |
| Approach: | a team of researchers has developed a framework to extract multimedia knowledge elements from scientific literature to combat COVID-19. |
| Outcome: | a new framework extracts fine-grained multimedia knowledge elements from scientific literature . it provides detailed contextual sentences, subfigures, and knowledge subgraphs as evidence . the framework is based on a case study of drug repurposing . |
Speak: A Toolkit Using Amazon Mechanical Turk to Collect and Validate Speech Audio Recordings (2022.lrec-1)
Copied to clipboard
| Challenge: | Speak is a toolkit that allows researchers to crowdsource speech recordings using Amazon Mechanical Turk (MTurk). |
| Approach: | They propose to use Amazon Mechanical Turk to crowdsource speech recordings . they use various measures to ensure that the recordings are of adequate quality . |
| Outcome: | Speak is an open-source toolkit that allows researchers to crowdsource speech recordings using Amazon Mechanical Turk (MTurk). |
Hidden Persuaders: LLMs’ Political Leaning and Their Influence on Voters (2024.emnlp-main)
Copied to clipboard
| Challenge: | This paper examines the political leanings of large language models (LLMs) in the 2024 election. |
| Approach: | They propose to use large language models to examine users' political leanings in the 2024 presidential election to determine their political preference. |
| Outcome: | The proposed models show that they have a political leaning and can influence political views in the 2024 presidential election. |
Structured List-Grounded Question Answering (2025.coling-main)
Copied to clipboard
| Challenge: | Document-grounded dialogue systems aim to answer user queries by leveraging external information. |
| Approach: | They propose a dataset to evaluate QA systems' ability to interpret and use structured lists . they use language models and model-based filtering processes to enhance data quality . |
| Outcome: | The proposed model outperforms baselines on the LIST2QA dataset . it shows that the proposed model is more accurate and complete than baselines . |