Yisong Miao | Web IR NLP Group @ NUS

LLMs Infer Cultural Context but Fail to Apply It When Responding

Sun, 25 Oct 2026 00:00:00 +0000

REPA: Reproducibility Evaluation via an Autonomous Pipeline Architecture

Tue, 07 Jul 2026 00:00:00 +0000

Yisong Miao Presents His Vector Institute Research Internship Work (with UBC NLP) at the NUS SRI Event

Thu, 02 Jul 2026 00:00:00 +0000

On the afternoon of 2 July 2026, NUS SoC held the 2026 edition of its Summer Research Internship (SRI) Research Gathering and Networking Event. SRI is our school’s program for attracting talent from around the globe to conduct research at our school over the summer. Our group is delighted to host Mr. Thura Aung (KMITL) and Mr. Ha Minh Hieu (HUST) this summer. Dr. Anand Bhojan delivered the opening remarks, and Prof. Chan Mun Choon gave a keynote about SoC’s PhD program.

Yisong Miao, a PhD student from our group, was invited to give a 20-minute presentation at the gathering. He shared his experience as a Vector Institute research intern in 2025, under the supervision of Prof. Vered Shwartz and Prof. Jian Zhu (both from the NLP Group at the University of British Columbia). This is the most interdisciplinary research Yisong has done, connecting pragmatic speaker models (closely related to his PhD topic of discourse) with LLMs’ cultural competence, language grounding, and vision language models. The project examines whether LLMs can act as pragmatic speakers by adapting their responses to users’ cultural backgrounds in conversations grounded in images. The team built Cultural and Pragmatic Response Inference (CAPRI), a new dataset in which users provide cultural cues and ask questions requiring culturally appropriate answers. For example, “What is the temperature?” should be answered in °C or °F depending on the user’s cultural background. Extensive evaluations show that state-of-the-art models can largely infer the user’s cultural background, but often fail to apply this knowledge in their responses. Explicit reasoning about the user’s background, step by step, improves their responses, but can be costly in real-time conversation. The work will appear at EMNLP 2026.

Yisong felt especially honored to give the première présentation of this work at this event, as SRI brings together junior students from around the globe, including Brazil, France, and the USA (which are also represented in the CAPRI dataset!). The seminar concluded with a discussion about future work on extending the CAPRI dataset to more cultures in Southeast Asia (where many seminar audiences come from) and elsewhere around the world.

Prof. Vered Shwartz said: “I’m really excited about this benchmark. Most of the existing work in cultural competence focuses on testing LLMs on their cultural knowledge. Our benchmark allows us to test whether LLMs can also recognize cultural context and apply this knowledge in context. I hope our work will inform future model design. At a personal level, it was a pleasure working with Yisong and Jian on this project. Yisong was always so methodological, organized, and energetic, even though our virtual meetings were happening at 1 am Singapore time. I hope to meet him in person soon!”

Links: Earlier news featuring Yisong as a Vector Institute research intern; The project indexed at our website.

Below is a gallery of the seminar photo

Yisong with the 2026 cohort of NUS SRI interns after the seminar:

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 Hosts a Lab Tour for AAAI 2026 Participants

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

AAAI 2026 has been held in Singapore from January 20 to January 27. Some of our group members are excited to travel to the conference site (at Expo) to communicate research. In conjunction with our regular group meeting on Friday, January 23, we are delighted to invite AAAI participants to visit our WING lab and experience the NUS Computing environment.

With our visitors, this group meeting had a special agenda:

Minzhi Li from WING NUS gave a presentation to debrief her 2025 internship experience.

Dr. Lu Gan (from GESIS - Leibniz Institute for the Social Sciences) gave a presentation about an AAAI paper from their team, titled “GSAP-ERE: Fine-Grained Scholarly Entity and Relation Extraction Focused on Machine Learning” (available here).

Finally, we had a round of self-introductions for all WING members as well as the visitors to socialize and discuss research.

Below is a gallery of the lab tour, photo credit to Sahaj, Yisong, and Min!

SSNLP 2026: WING Members Present Three Posters

Wed, 21 Jan 2026 00:00:00 +0000

The Singapore Symposium on Natural Language Processing (SSNLP) returns on Wednesday, January 21, 2026, at SUTD as a full-day, in-person event. Since 2018, SSNLP has been the annual gathering of Singapore’s NLP community, bringing together students, faculty, and industry researchers to share ongoing work and spark collaboration. Held in conjunction with AAAI 2026, this year’s symposium will feature invited keynotes from leading researchers in the field, a panel discussion, and an immersive poster-focused program showcasing recent work from Singapore-based researchers published in top venues such as ACL, EMNLP, NeurIPS, ICLR, and AAAI this year (this short intro is propagated from SSNLP 2026 website).

WING members are delighted to attend the seminar, enjoying keynote talks from guest researchers who travel all the way from AoE to Singapore. We also appreciate the panel discussions led by PC Chairs (from *ACL, ICLR, and NeurIPS conference), who share valuable insights on the peer review process, particularly from the students’ perspective.

We also engage in the immersive poster program, and our group is excited to present three posters:

Discursive Circuits: How Do Language Models Understand Discourse Relations? by Yisong Miao and Min-Yen Kan (EMNLP 2025)
SkyLadder: Better and Faster Pretraining via Context Window Scheduling by Tongyao Zhu, Qian Liu, Haonan Wang, Shiqi Chen, Xiangming Gu, Tianyu Pang, and Min-Yen Kan (NeurIPS 2025)
Drifting Away from Truth: GenAI-Driven News Diversity Challenges LVLM-Based Misinformation Detection by Fanxiao Li, Jiaying Wu, Tingchao Fu, Yunyun Dong, Bingbing Song and Wei Zhou (AAAI 2026).

We thank the symposium organizers for the opportunity to present our work, as well as the enthusiastic audience who engaged with us during the poster sessions!

Below is a gallery of the poster presentations, we thank Prof Min for taking these photos!

Yisong presenting his work on “Discursive Circuits: How Do Language Models Understand Discourse Relations?”:

Tongyao presenting his work on “SkyLadder: Better and Faster Pretraining via Context Window Scheduling”:

Fanxiao presenting his work on “Drifting Away from Truth: GenAI-Driven News Diversity Challenges LVLM-Based Misinformation Detection”:

Yisong featured as a Vector Institute Intern

Mon, 08 Dec 2025 00:00:00 +0000

Check out 👀 Yisong Miao’s feature as a Vector Institute research intern in the latest 2025 installment of their news cast. Although he wasn’t able to travel to the institute in 🇨🇦 for the immersive physical part, WING is proud that he was able to participate in the programme while staying on the other side of the world!

Yisong mentored with Vector’s Vered Shwartz to understand why LLMs assume certain contexts and what helps them adapt to different cultures in what was his “most interdisciplinary project ever.” As a Vector intern, Yisong also got to network with IMPACT mentors. We wish him continued success in his research work as he continues his work at WING.

see the original LinkedIn post

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.

WING's CS6101 Retrieval Augmented Generation comes to a successful close at 27th STePS

Wed, 12 Nov 2025 00:00:00 +0000

WING ran an experimental section of our CS6101 Exploration of Computer Science Research, as a trial course on Retrieval Augmented Generation.

RAG is now a common gateway experience for the general public as well as students to experience Information Retrieval, a core research area of WING.

The CS6101 course website has publicly-available lecture slides, video lecture recordings and scribe notes for the class’s topics.

These include sections on LLM generation, Retreival, Ranking, RAG Models, Iterative Retrieval and Advanced RAG topics (inclusive of graph, multimodal RAG) and source credibility estimation.

Check out the LinkedIn posts by class participants Vangmay Sachin, Jonathan Chen and Sahej Agrawal.

You can also visit the other WING Events, including past public iterations of WING’s CS6101 sections.

Image enhanced and regenerated via Google’s Nano Banana

Discourse and LLMs

Tue, 04 Nov 2025 00:00:00 +0000

Large language models (LLMs) can now generate coherent text, but can they truly understand language? In this project, we explore discourse understanding, a foundational objective in natural language processing (NLP). In the first part, we refine the notion of understanding as faithful behavior under a series of Socratic-style questions (appeared at ACL 2024). In the second part, we take a causal approach to mechanistically interpret the key components of transformer models in discourse processing (appeared at EMNLP 2025).

Yisong, a PhD student at WING, began his research journey by tackling the fundamental question: Do language models truly understand text? Over time, he refined this broad inquiry into the specific challenge of discourse understanding. In his recent work, advised by Prof. Min, they introduced a more precise framework for measuring discourse comprehension from three discourse-specific perspectives, while also contributing insights into broader LLM challenges such as logical consistency. Currently, Yisong and Min are delving deeper into the mechanisms behind how models process and understand discourse, and they discovered that sparse computational graphs, termed as “discursive circuits”, control how models process discourse relations.

Discursive Circuits: How Do Language Models Understand Discourse Relations?

Tue, 04 Nov 2025 00:00:00 +0000

CS6101 T2510 - Retrieval Augmented Generation

Thu, 07 Aug 2025 00:00:00 +0000

Assessing the AI Scientist

Mon, 26 Aug 2024 00:00:00 +0000

Our collaboration with Joeran Beel and Moritz Baumgart of ISG Siegen originated from Joeran’s sabbatical visit with WING in Oct 2024. Moritz, a talented undergraduate student at University of Siegen, joined us as a research assistant, working remotely which coordinated with his advisor here in NUS.

Over the course of Joeran’s visit, we were able to install and test the AI Scientist system advertised as an automated robo scientist by Sakana.AI. We find positive use cases, but also weaknesses that need much handholding from us.

Haomeng, Rui Feng and Nura join our team as students working towards assessing the growing variety of LLM based research agents going into 2025.

Yisong Miao receives the Senior Area Chair Award at ACL 2024!

Thu, 15 Aug 2024 00:00:00 +0000

Congratulations to WING members, Yisong Miao, Min-Yen Kan, and their collaborators for winning the Senior Area Chair Award at the 62nd Annual Meeting of the Association for Computational Linguistics (ACL 2024) for their paper, “Discursive Socratic Questioning: Evaluating the Faithfulness of Language Models’ Understanding of Discourse Relations.”

Our group is thrilled to announce that we have received a Senior Area Chair Award (Discourse and Pragmatics track) at ACL 2024 for our paper, “Discursive Socratic Questioning: Evaluating the Faithfulness of Language Models’ Understanding of Discourse Relations.” This work, led by our group members Yisong Miao and A/P Min-Yen Kan, in collaboration with Hongfu Liu, Dr. Wenqiang Lei, and Dr. Nancy Chen, introduces a novel scoring framework that leverages LLMs in a Socratic style, testing models on targeted questions, counterfactuals, and converse questions.

Learn more about this paper.

Discursive Socratic Questioning: Evaluating the Faithfulness of Language Models’ Understanding of Discourse Relations

Sun, 11 Aug 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.

Emoji Composition

Mon, 20 May 2024 00:00:00 +0000

The project began when Yisong, intrigued by the Emoji Mashup Bot, explored the question: Can emojis be composed to convey meanings like English phrases? With the support of his advisor, Prof. Min, he recruited an undergraduate student, Zi Yun Yang, to collaborate on the project. Ms. Yang built an annotation platform to collect emoji compositions and their corresponding English phrases from her peers. After her graduation, Yisong and the team added another layer of annotation on composition types and formalized an emoji-based textual entailment task (EmoTE).

The first iteration of this work was published at LREC-COLING 2024. Prof. Min was not listed as an author due to his role as a conference chair, but this project cannot be finished without his guidance. The project continues to gain interest, particularly among undergraduates, with many students from our local NLP course using the emoji dataset for their final projects.

The ELCo Dataset: Bridging Emoji and Lexical Composition

Mon, 20 May 2024 00:00:00 +0000

Visualising Large Language Model Activations

Fri, 17 May 2024 00:00:00 +0000

In the field of natural language processing, large and complex neural networks, particularly transformers, have become essential due to their effectiveness in handling text data. However, despite their success, current methods for visualizing how activations of specific network units influence model outputs remain underdeveloped. This gap hinders interpretability and limits researchers’ and practitioners’ understanding of neural network behaviors during training and inference.

This project aims to address this issue by creating a robust visualizer tailored for transformer architectures. By processing training or test data, this project seeks to track and analyze changes in attention scores and other structural components of the transformer network, visualizing their evolution within individual input sentences during inference. The project involves developing innovative visualization conventions to compactly represent the high-dimensional neural network processes in a manner that is analytical and accessible, through the usage of static diagrams.

CS6101 2310 - Large Language Models

Sun, 06 Aug 2023 00:00:00 +0000

Comparative Snippet Generation

Sun, 01 May 2022 00:00:00 +0000

CS6101 2020 - Conversational Recommendation Systems

Wed, 06 Jan 2021 00:00:00 +0000

Estimation-Action-Reflection: Towards Deep Interaction Between Conversational and Recommender Systems

Wed, 01 Jan 2020 00:00:00 +0000