Headed to #ACL2019 in Florence, Italy? Join IBM researchers, to learn how to translate table into natural language, on July 28th. T9 "Storytelling from Structured Data and Knowledge Graphs: An NLG Perspective" Learn more here ➡️ bit.ly/nlg-acl19

This year at #acl2019nlp, IBM Researchers will present technical papers describing the latest results in our long-term push to help #AI systems master language. Read the papers here: ibm.co/2YmAo2y

IBM Research has about 21 accepted (2 workshop) papers at #emnlp2019 ! Come and talk to us to know more about the papers or if you're looking for summer internships or job opportunities. I'm looking to find someone interested to work on Question Answering!

IBM Research Remaining papers are here..

IBM Research AI launched a new question answering leaderboard for domain adaptation for enterprise QA systems. medium.com/@sroukos/quest… #ml #questionanswering #TechQA

IBM Research #AI is at #NeurIPS2019. Stop by and try our tech, or learn more about the work our scientists are featuring ➡️ibm.co/2P7IDON

#nlp at work on #covid for research on it.

Helped writing this article about IBM Research 's presence at ACL 2020. We've 19 papers accepted at the main conference and we'll show live demos of these systems in action! Come visit us next week July 6 -8 at our virtual booth. #acl2020 #NLProc ibm.com/blogs/research…

Semantic parsing for Knowledge Base Question Answering. Exciting times! linkedin.com/posts/salim-ro…

check it out. Systems that learn and reason.

Interesting use of AMR parsing (Abstract Meaning Reprsentation of language) for knowledge base question answering #nlp #knowledge

exciting #NLP tech

If you're using GPT-3 or any other LLMs read this: 1. Don't want it to hallucinate? 2. Need attribution for generated answers? 3. Have access to proprietary data that you want to index yourself and generate answers from it? Use PrimeQA! We added "retrieve" and "read" mode.🧵

#acl2023 findings paper for folks working on retrieval leaderboards- Read on: ✅ We show multi-dimensional tradeoffs e.g. quality , latency & cost (instead of just F1) ✅ Metrics that include concrete efforts e.g. DynaScore. -- Code in PrimeQA: github.com/primeqa/primeqa