Yajing Yang | Web IR NLP Group @ NUS

AnalysisBank: An Expert Analysis Pattern Library for Financial Report Generation

Tue, 01 Sep 2026 00:00:00 +0000

CIVIC-AI: Stanford's SALT Lab and WING.NUS Collaborate on Social Intelligence and the Future of AI and Work

Mon, 22 Jun 2026 00:00:00 +0000

The inaugural CIVIC-AI workshop (13–14 July 2026) kicks off a major collaboration between Stanford’s SALT Lab and WING.NUS, bringing together researchers, policymakers, and funding agencies to examine the Social Intelligence of Foundation Models and the Future of AI and Work.

The CIVIC-AI Workshop is an upcoming two-day event in Singapore that will explore the profound societal impacts of AI adoption. The workshop is generously funded by the Ministry of Digital Development and Information of the Republic of Singapore under its AI Visiting Professorship grant, and is also supported by the Ministry of Manpower.

The event centers on three core questions:

Cross-cultural Dimensions: How do cultural context, economic development, and policy environments shape AI adoption and the lived experience of automation across different societies?
Future of Work & Automation: Which professions and tasks are being automated away versus augmented, and who bears the costs of displacement?
Human Advantage: What constitutes irreducible human value when a large fraction of knowledge work can be automated, and how do we measure and support it?

The first day (13 July) focuses on the theme of Social Intelligence, featuring invited talks by researchers such as Yohan Jo, Nancy F. Chen, and Lizi Liao, alongside lightning talks and a panel discussion. The highlight of the day will be a keynote by Diyi Yang from Stanford’s SALT Lab on “Optimizing Human-AI Collaboration,” which will introduce General User Models (GUMs) and Next Action Prediction (NAP) to foster proactive and meaningful human-AI interaction.

The second day (14 July) will center on the Future of Work With AI Agents in Singapore, featuring presentations by Diyi Yang and Min-Yen Kan, followed by extensive discussion sessions to finalize directions and next steps for the collaboration.

Registration for the workshop closes on 6 July 2026. For more details and to register, visit the CIVIC-AI workshop website.

The workshop is made possible by the Singapore Global AI Visiting Professorship (AIVP), an initiative by the Ministry of Digital Development and Information to strengthen Singapore’s AI research capabilities by attracting world-class expertise. Min-Yen Kan (WING.NUS) and Diyi Yang (SALT Lab, Stanford University) are among six NUS Computing faculty teams awarded AIVP grants, for their project “Evaluating and Building Socially Intelligent Foundation Models” — the research collaboration that underpins CIVIC-AI.

WING 2026 Spring Outing at Clarke Quay

Fri, 23 Jan 2026 00:00:00 +0000

WING members were excited to have a spring outing at Clarke Quay on January 23, 2026. For this outing, we scheduled it at the beginning of the semester to help new members better cohere with the group.

We enjoyed both the beautiful river view and the pizza! We were happy to see the return of our alumni, especially Hengchang, Victor, and Taha, as well as our collaborator, Yunshan. We especially thank Hengchang (a WING PhD alumnus) for his generous donation of the pizza (and other items on the bill as well)!

Below is a gallery of the outing, photo credit to Yajing, Glenda, and Yisong!

WING Members Present at NUS AI Seminar at the Computer Science Department

Wed, 19 Nov 2025 00:00:00 +0000

NUS AI Seminar at the Computer Science Department is a new initiative to bring together AI researchers to share their latest research findings and insights. There are eight speakers in the Fall 2025 semester, usually hosted on Wednesday afternoons at Seminar Room 21. WING members are excited to present their research alongside other presenters from NUS Computing, MIT, and UCLA. We appreciate Prof. Lee Wee Sun and PhD student Guoji Fu for hosting the seminar.

Yisong Miao gave a seminar presentation titled “Faithfulness and Interpretability for Discourse Understanding” on November 19th, 2025. This talk combines his work on Discursive Socratic Questioning (ACL 2024) and Discursive Circuits (EMNLP 2025). He explained how our team tackles the technical challenge of evaluating a model’s discourse faithfulness and formalizing a unique setup for transformer circuit discovery. The seminar ends with an audience discussion on the conceptual difference between truthfulness and faithfulness, as well as designing new methods using sparse circuits in future work.

Yajing Yang presented “From Data to Insights: LLMs for Financial Narration”, also on November 19th, 2025, highlighting her research on financial data narration. Drawing from DataTales: A Benchmark for Real-World Intelligent Data Narration (EMNLP 2024) and KAHAN: Knowledge-Augmented Hierarchical Analysis and Narration for Financial Data Narration (EMNLP 2025), she described our team’s efforts to build a realistic benchmark and improve generation quality through knowledge integration and hierarchical analysis. The talk sparked discussion on remaining challenges in financial report generation and how LLMs could be used to produce more actionable and informative insights.

On December 3rd, 2025, Xuan Long Do delivered a seminar titled “Toward Autonomous Self-Improving Foundation Models”. The presentation spanned multiple projects, including “What Makes a Good Natural Language Prompt?” (ACL 2025), Multi-Expert Prompting (EMNLP 2024), and VISTA, his 2025 Google internship project on a self-improving video generation agent. Beginning with an analysis of prompt and model fragility, he showed how multi-agent reasoning can help address these limitations before moving toward the broader vision of autonomous self-improving foundation models. The seminar concluded with an audience discussion on future research directions in this area.

Below is a gallery of the seminar photos, some of which are enhanced and regenerated via Google’s Nano Banana

Yisong Miao presenting his work on “Faithfulness and Interpretability for Discourse Understanding” at the AI Seminar on November 19th, 2025:

Yajing Yang presenting her work on “From Data to Insights: LLMs for Financial Narration” at the AI Seminar on November 19th, 2025:

Xuan Long Do presenting his work on “Toward Autonomous Self-Improving Foundation Models” at the AI Seminar on December 3rd, 2025:

WING Members Present at NUS Computing's Inaugural AI-X: Industry Day

Tue, 18 Nov 2025 00:00:00 +0000

A gallery of additional photos from the event is included below, with thanks to the official event photographer.

WING Members Enjoy the Group Outing at the Macritchie Reservoir

Fri, 14 Nov 2025 00:00:00 +0000

A gallery of additional photos of the outing is included below.

KAHAN: Knowledge-Augmented Hierarchical Analysis and Narration for Financial Data Narration

Wed, 05 Nov 2025 00:00:00 +0000

Analytical Report Generation with LLMs

Tue, 12 Nov 2024 00:00:00 +0000

While LLMs excel in language understanding and can pass professional financial examinations, they struggle to generate expert-level analytical reasoning from real data. In this project, we explore analytical report generation using LLMs, turning complex market data and corporate disclosures into actionable, decision-relevant narratives. We first develop DataTales (EMNLP 2024), a benchmark pairing 4.9k financial market data tables with human reports to diagnose the exact gap between LLM generation and human creation. Secondly, we propose KAHAN (Findings of EMNLP 2025), a knowledge-augmented hierarchical analysis framework that coordinates analysis from entity metrics to market-wide patterns using executable code. Thirdly, we introduce AnalysisBank (EMNLP 2026), a distilled library of over 5,300 expert analysis patterns that conditions reasoning directly on observed data signals to generate novel, data-specific insights.

Yajing, a PhD student at WING and a Senior Data Scientist at Rio Tinto, started her research driven by the real-world business need for timely daily market reports. While working alongside market professionals, she observed how human commentary takes hours to draft while existing automation defaults to shallow summaries. Advised by Prof. Min-Yen Kan, she formalized this industry pain point into a systematic study of execution failures in generative models. Together with their collaborators, they developed structured methodologies to decouple calculation from composition and condition reasoning moves directly on observed data patterns. Their work demonstrates that grounded analytical depth can be systematically achieved across financial modalities and transferred to domains like medical diagnostics and scientific writing.

DataTales: A Benchmark for Real-World Intelligent Data Narration

Tue, 12 Nov 2024 00:00:00 +0000

WING Members Enjoy the Group Outing at Yajing's Condo for a BBQ

Fri, 26 Jul 2024 00:00:00 +0000

A gallery of additional photos of the outing is included below.

Scientific document processing: challenges for modern learning methods

Fri, 24 Mar 2023 00:00:00 +0000

Lightweight Contextual Logical Structure Recovery

Sat, 01 Oct 2022 00:00:00 +0000