Understanding the Web
22nd October 2023,University of Birmingham, UK
Rajeev Gupta (Principal scientist, Microsoft, India)
Microsoft R&D India Pvt. Ltd., Hyderabad, India
Email: rajeev.gupta@microsoft.com
22nd October 2023,University of Birmingham, UK
22nd October 2023,University of Birmingham, UK
Workshop Venue: Teaching and Learning Building (M208/M209) at the University of Birmingham (workshop venue).
The below schedule is based on UK time zone(UTC+1).
Session 1: 9.00-10.30
| Introduction & Initial announcements: 9.00-9.30 |
| Lessons from the age of user-generated content for the age of AI-generated content (Prof. Nishanth Sastry: 9.30 to 10.30 ) |
| Refreshment Break: 10:30-11:00 |
Session 2: 11.00-12.30
| Enhancing Enterprise Knowledge Base Construction with Fine-Tuned Generative Language Models (Liana Mikaelyan:11.00-11.45) |
| Research Session 1: 11.45 – 12:30 1. Related Table Search for Numeric data using Large Language Models and Enterprise Knowledge Graphs(Pranav Subramaniam, Udayan Khurana, Kavitha Srinivas and Horst Samulowitz) 2. Cognitive Retrieve: Empowering Document Retrieval with Semantics and Domain Specific Knowledge Graph(Apurva Kulkarni, Chandrashekar Ramanathan and Vinu E Venugopal) |
| Lunch: 12.30- 14.00 |
Session 3: 14:00- 15:30
| Building Knowledge Graph for Products at Scale and infusing it into LLMs(Dr. Manoj Agarwal: : 14.00-14.45) |
| Research Session 2:(14.45 -15.30) 1. EduEmbedd – A Knowledge Graph Embedding for Education(Anurag Mohanty) 2. CRUSH: Cybersecurity Research using Universal LLMs and Semantic Hypernetworks (Mohit Sewak, Vamsi Emani and Annam Naresh) |
| Refreshment Break: 15.30 – 16.00 |
Session 4: 16.00- 17:00
| LLMs for Social Networks: Applications, Challenges and Solutions (Bojan Babic: 16.00-17.00) |
22nd October 2023,University of Birmingham, UK
| Abstract Submission: |
| Paper submission : |
| Notification of paper acceptance : |
| Camera Ready Paper Submission : 1st October 2023 |
| The workshop : 22nd October 2023 |
22nd October 2023,University of Birmingham, UK
Lessons from the age of user-generated content for the age of AI-generated content
Prof. Nishanth Sastry, Director of Research of the Department of Computer Science, University of Surrey.
Abstract:
The past decade and more has been defined by the rise and near universal adoption of user-generated content (UGC) on social media. Initial excitement about the promise of UGC has since become tempered by concerns about misinformation, hate speech and other online harms. We are now witnessing a similar enthusiasm for content generated by Large Language Models. This talk will draw parallels between the two, and extract lessons about the perils, potentials and pitfalls awaiting us in the future age of AI-generated content.
Biography:
Prof. Nishanth Sastry is the Director of Research of the Department of Computer Science, University of Surrey. His research spans a number of topics relating to social media, content delivery and networking, and online safety and privacy. He is joint Head of the Distributed and Networked Systems Group and co-leads the Pan University Surrey Security Network. He is also a Surrey AI Fellow and a Visiting Researcher at the Alan Turing Institute, where he is a co-lead of the Social Data Science Special Interest Group.
Can machines discover new knowledge?
Dr. Fabio Petroni, Co-Founder & CTO at Samaya AI
Abstract:
For many years, the quest to determine the most efficacious representations of knowledge for machines has been at the forefront of research. Historically, this focus has centered on knowledge retrieval, whether from unstructured text corpora, structured collections (e.g, knowledge graphs, key-value memories), or the parameters of a neural model. How can we evolve these representations to not just retrieve, but actively discover new knowledge?
Biography:
Dr. Fabio Petroni is the Co-Founder & CTO at Samaya AI, building an AI-powered knowledge-discovery platform. Before that he was a Researcher at FAIR and Thomson Reuters, focusing on representing, gathering, extracting, using, reasoning on and creating world knowledge using AI.
Enhancing Enterprise Knowledge Base Construction with Fine-Tuned Generative Language Models
Ms. Liana Mikaelyan, Research Software Development Engineer in the Alexandria team, Microsoft Research Cambridge UK .
Abstract:
In this talk, we will present our latest work on leveraging the power of generative language models for knowledge base construction. We have fine-tuned a generative LLM to extract entities and their relevant properties from text passages and represent them in a structured JSON format. This task was accomplished by creating a dataset of short passages and corresponding JSON outputs using GPT4, which was then used to fine-tune the OpenLlama 3B model on a single A100 GPU. Our approach has demonstrated superior performance compared to the existing template matching algorithm in Alexandria, both in terms of precision and coverage, as well as extracting a richer set of properties from the text. Furthermore, the addition of new properties to the knowledge base has been significantly simplified. Future work involves exploring ways to improve the generation time as well as investigating other models to further enhance our system’s performance
Biography:
Ms. Liana Mikaelyan is a Research Software Development Engineer in the Alexandria team at Microsoft Research Cambridge UK . Before joining Microsoft Research Cambridge she worked on various machine learning projects mainly in speech synthesis and recognition. She completed her MSc in Machine Learning at UCL with a background in mathematics.
LLMs for Social Networks: Applications, Challenges and Solutions
Bojan Babic, Nextdoor.
Abstract:
Last couple of years we have witnessed an explosion of Generative AI research and respective applications that are simultaneously transforming how companies operate internally and how they communicate with their customers.
In this talk we will present work of the Nextdoor GenAI team and respective LLM applications in social networks in the areas such as Knowledge tasks, Engagement tasks and Governance. We will cover what we have tried, what works and what does not work. At the same time, in this talk we will present a framework that we used that helped us iterate fast and systematically improve each of the product areas.
Biography:
Bojan Babic is currently working on various Generative AI problems at the social media platform Nextdoor. Preceding this position, he has been working on the Search/Information Retrieval, Ads and recommendations and respective application spanning from e-commerce to social media space
Building Knowledge Graph for Products at Scale and infusing it in to LLMs
Dr. Manoj Agarwal,Senior Staff Engineer in Discovery Intelligence team at Uber AI.
Abstract:
A knowledge graph is the key to entity search as it can store the factual entity related information in a structured manner without the rigidity of a fixed schema. Both Google and Bing have web scale knowledge graphs and for a large fraction of user queries knowledge graph is invoked. E-commerce search is primarily an entity search. Therefore, building a Knowledge Graph is the key to improve the eCommerce search in many ways. However, building it at web scale is a highly challenging problem. It is an equally or even more challenging problem to build the knowledge graph for products. In this talk, we present our methodology to build the knowledge graph for products at web scale. With recent success of LLMs, can we infuse such semantic understanding of the world, encoded in the form of Knowledge Graph, in the LLMs? There are some advances in this direction, however it remains an open question if the Knowledge graphs can be replaced by the LLMs.
Biography:
Dr. Manoj Agarwal is Senior Staff Engineer in Discovery Intelligence team at Uber AI. Before Uber, he was Principal Applied Scientist at Microsoft – AI and Research and a senior researcher in IBM Research. Manoj was the chief architect for building a web scale product knowledge graph for Microsoft – Shopping, comprising a few hundred million products and a few billion facts with high accuracy. Currently, he is engaged in the efforts to build the scalable knowledge graph as well as discovering the taxonomy to improve the semantic search and recommendations for Uber Delivery. His research interests are in the areas of web mining, graph mining, pattern recognition, data mining, knowledge graphs, LLMs and information retrieval with more than 30 patents and over 25 research papers in reputed journals and conferences.
22nd October 2023,University of Birmingham, UK
Knowledge graphs can integrate diverse data sources and provide a holistic view to the downstream applications. By virtue of being structured, knowledge graphs offer transparency and interpretability to the search and recommendations applications. Combining Knowledge Graphs with current-day advances in LLMs can create several opportunities.
The EKG-LLM workshop as part of CIKM 2023, would be addressing how large language models can help with the construction and usage of these enterprise knowledge graphs. This involves improving all the aspects of EKG workflow using large language models: entity extraction, entity enrichment, EKG construction, querying EKG for search and recommendations, scenario specific EKG, etc. Through this workshop we would like to highlight research issues specific to the integration of the enterprise knowledge graphs with large language models and associated applications.
Topics of interest include but are not limited to, the following:
Manuscripts should be submitted in PDF format with 6 pages of content , plus references. Please follow two-column CEUR style template (https://ceur-ws.org/Vol-XXX/) for paper submissions .
Link for paper submission: https://easychair.org/conferences/?conf=ekgllm2023
Authors of accepted papers should prepare a camera-ready (final) version of their paper and submit it using the EasyChair system no later than Sunday, October 1, 2023. Please email the camera ready version(PDF as well as editable versions (doc/latex)) to rajeev.gupta@microsoft.com , sri@iiitb.ac.in, aparna.m@iiitb.ac.in and bhoomika.ap@iiitb.ac.in.
Each accepted paper requires at least one author to perform in person registration using the link https://uobevents.eventsair.com/cikm2023/cikmauthpreandmain and be presented at the workshop in-person in order to include and publish the paper in the workshop proceedings.
Preparation of Camera Ready Paper
Authors are advised to address the comments of the reviewers in the camera-ready version suitably.
Camera Ready version should be prepared using the two-column CEUR style template (https://ceur-ws.org/Vol-XXX/) and it must adhere to the instructions specified at : https://ceur-ws.org/HOWTOSUBMIT.html#CEURART
Background :
Policymakers are people who are responsible for formulating policies and making policy decisions. UN has come up with 17 Sustainable development goals across domains with around 167 targets to transform the world. And it is upon policymakers, government officials, researchers, and data scientists to help achieve these sustainable targets by identifying key problem areas and their factors, collecting, processing, and analyzing relevant historic and current data to provide necessary insights to make informed decisions by designing policies for sustainable development.
Karnataka Data Lake is an ongoing project serving as the Data Analytics partner for the Department of Planning and Statistics, Karnataka.
This activity brings you an exciting opportunity to be a Policymaker for a day
If you’ve made a PolicyMaker for a day 🤔, how do you approach, understand and resolve the problem? 🧐 What policy and budget decisions will you make to build a sustainable society and achieve an SDG target? 🤓
The Task :
The activity requires participants to be divided among groups.
Each group is presented with a problem statement for a region. Considering the data and analysis provided by the KDL site or any other sources, the team should design the policies to help achieve the UN’s Sustainable development target not limited to the below questions but can be based on your expertise.
By the end of the activity, each group should present a case study by performing the below tasks ✅
(A sample Example is provided for reference purposes.)
References :
Please form groups based on your familiarity with the below SDG Goals. Through this activity, we would love to hear your group’s narratives in solving and achieving the SDG targets not limited to just using the dashboards, but any research papers/reports/news articles/personal or professional expertise.
(*Please note that our volunteers will be around in case of queries or if any help is required to solve/present the problem)
Aug 2023 : Open
One Post-doctoral position for 1 year is open, starting from August 1, 2023 for Karnataka Data Lake project : Policy Research using Big Data Analytics (https://kdl.iiitb.ac.in). The position may be extended based on requirement and performance.
The Key responsibilities include the following :
Interested candidates may send their CV along with 2-3 publications to sri@iiitb.ac.in.
Jan 2023: Closed
3-month internship in visual analytics and predictive modelling
Two positions for 3-month paid internships are open, starting January 15, 2023 till April 14, 2023. The positions may be extended for 3 more months based on requirement and performance.
Internship applicants should have a BTech or equivalent in Computer Science or related disciplines like Information Technology, Data Science, etc. Programming proficiency in python is highly desirable, and experience with visual analytic tools like Tableau or Kibana is an added plus.
Interns will get an opportunity to work on a major project involving planning and resource allocation, and pick up skills like Bayesian modelling, building data stories and providing actionable insights.
The internships will come with a stipend of INR 15,000 per month. Applications may be sent to sri@iiitb.ac.in
Dec 2022: Closed
Project Elective applications are open to work on various WSL projects for the upcoming Jan-Apr 2023 semester at IIIT-Bangalore. Students can apply for 4-credit, 12-credit or 20-credit projects as applicable. This call is open to students currently enrolled at IIIT-B.
Applications will close on 2nd Dec 2022. If applied after 2nd Dec, we will reach out to you only in case there are any further open positions.
Project details available here: https://drive.google.com/file/d/1So1fm1Zeu0aaZHGQMC_vWd2efaRLvoko/view?usp=sharing
Form to apply: https://forms.gle/Cy8SzNNp5Y3szhy79
WS4D Datathon http://cognitive.iiitb.ac.in/ws4d-datathon-and-phd-colloquium/
Data:
The key dataset(s) pertain to information gathered from India, and provided by the Red Dot Foundation.
Reference articles https://safecity.in/publications/research-papers/ pertain to the following topics:
Challenge themes:
The following points are for processing data and analyzing it deliberately, and using the knowledge to create a compelling visualization as a narrative/summary (preferably) or a tool. The visualization (tool) must be shareable on social media to spread awareness and to inspire action against gender-based violence and others.
For Theme-MythBusters, relevant myths (as a sample):
For Theme-MirrorMirrorOnTheWall, relevant datasets and sources:
https://data.oecd.org/inequality/violence-against-women.htm
For Theme-Mash-up, relevant datasets and sources:
Deliverables:
A compelling visual narrative to be shared on social media:
For further queries: datathon2020@iiitb.ac.in
Feb 14, 2020 | 10AM to 4PM | IIIT-Bangalore
Register HERE
The goal of this session is to have research discussion among the PhD research scholars across multiple institutes who are working in the areas related to Web Science. We hope these discussions will be useful and will foster research collaborations in future!
Moderators: Faculty
Panelists: PhD Research Scholars
Audience: Research Scholars
