We are seeking for a principle way to connect the learning power and generalizability of neural networks, with the rationale thinking and transferability of logic languages. There is a long way to go. But the adventure ahead is so fascinating.
A poster by Quan Guo, research associate in computer science @michiganstateu, was named “Most Impactful to AI” during the AI For Society Symposium at University of Michigan on Oct. 19. He is supervised by Computer Science Assistant Professor Parisa Kordjamshidi.
Mind-blowing project that spins up a complete website—frontend, backend, database, user login, and more—using just ONE prompt! 🤯 This takes the dev agent battle to a whole new level. Can’t believe how far AI-driven dev has come!
NeurIPS acknowledges that the cultural generalization made by the keynote speaker today reinforces implicit biases by making generalisations about Chinese scholars. This is not what NeurIPS stands for. NeurIPS is dedicated to being a safe space for all of us. We want to address the comment made during the invited talk this afternoon, as it is something that NeurIPS does not condone and it doesn't align with our code of conduct. We are addressing this issue with the speaker directly.
NeurIPS is dedicated to being a diverse and inclusive place where everyone is treated equally.
@NeurIPSConf#NeurIPS is known for being an inclusive and respectful community https://t.co/BLMyoOzMhW that values diversity—after all, it even changed its name to avoid causing offense https://t.co/kFmHaXN2Wg
#NeurIPS is known for being an inclusive and respectful community https://t.co/BLMyoOzMhW that values diversity—after all, it even changed its name to avoid causing offense https://t.co/kFmHaXN2Wg
🚀 Excited to see this comprehensive survey on the latest in VLN! 📚 Great work @zhan1624 ! The rapid advancements in LLMs and VLMs are indeed opening up new frontiers. Looking forward to exploring the insights and future possibilities. #VLN#AI#Research
Thrilled to share our survey paper on Vision-and-Language Navigation! We categorize the challenges of VLN, considering the strengths of foundation models. We welcome any feedbacks or insights to further perfect our work.
📣 I’m on the academic job market this year! I am broadly interested in #MachineLearning (ML) and #DataScience, especially in graph ML, data-centric AI and trustworthy AI, with applications in computational biology and social good. RT appreciated! https://t.co/2V6AKNfgbY
🧑🎓I passed the Ph.D. dissertation defense! The Ph.D. cap is awesome! I would like to express my sincere appreciation to my advisor Dr. Parisa Kordjamshidi, committee members, HLR labmates, Friends, and Family!
🧑🎓I passed the Ph.D. dissertation defense! The Ph.D. cap is awesome! I would like to express my sincere appreciation to my advisor Dr. Parisa Kordjamshidi, committee members, HLR labmates, Friends, and Family!
@hardmaru@LambdaAPI Curious about the optimal airflow setting. We usually build the CPU fan horizontally in combination of the rear fan, such that the cool air come from the front and hot air flee directly from the rear. Guess there are guys tested different setting. But I don't have an idea.
Three years in a row, we are presenting with MAIS, receiving support from participants, and continuously pushing forward on this idea and towards a better AI integrating symbolic inference and deep feature learning! Exciting to be part of it!
Honored to announce that DomiKnowS won the first place poster award at Michigan AI Symposium. Learn more about this cool knowledge integration with deep learning framework in our website.
https://t.co/Q69ABhV98J
#NLProc#AI#MachineLearning#HLR#EMNLP2021
Our CLeaR workshop! on "Combining Learning and Reasoning: programming languages, formalisms, and representations" will be @RealAAAI, #AAAI2022. Check out [https://t.co/Ync3VqgVnK], stay tuned for more details. @BehrouzBabaki @sebdumancic @hfaghihi15@guyvdb@DanRothNLP
EMNLP-2021 Demo paper accepted🥳:1st version of DomiKnowS lib. released. To include domain knowledge (hard/soft, logical/linear constraints) with deep architectures(PyTorch) & use various algorithms based on same declarative specs. https://t.co/sWgLgBfGAY #EMNLP2021#NLProc
Our tutorial on "Representation, Learning and Reasoning on Spatial Language for Downstream NLP Tasks" videos: https://t.co/LXogr3lCgj. slides: https://t.co/MGGR6rScCI. Looking forward to the live QA: Nov 20, 12:00-13:00 OR 19:00-20:00 EST.@jamespusto@emnlp2020#NLProc#emnlp2020