Excited to be in Montreal this week for COLM 2025!
I have two papers accepted this year:
1️⃣ The Unlearning Mirage, a dynamic framework for evaluating LLM unlearning.
2️⃣ With @Harsh_N_Lalai10, using 20 Questions as a creative framework to systematically evaluate geographical bias in LLMs.
Check out the individual threads!
🚨 New paper alert! 🚨
Can you believe it? Flawed thinking helps reasoning models learn better!
Injecting just a bit of flawed reasoning can collapse safety by 36% 😱 — but we teach large reasoning models to fight back 💪🛡️.
Introducing RECAP 🔄: an RL post-training method that trains models to override unsafe reasoning, reroute to safe & helpful answers, and stay robust — all without extra training cost.
✨ Safer reasoning 🤖
✨ Stronger jailbreak resistance 🔓
✨ Lower overrefusal 🙅
✨ Preserved core reasoning capability 🧠
#LLM #ReasoningModels #RLHF #AISafety #Alignment #MachineLearning
🚨 NeurIPS 2024 🚨How robust are our AI-Generated Image Detectors?
🤔 Can they detect various magnitudes of image augmentations?
💡 Does performance fluctuate across scenes and subjects?
🚀 Find out with Semi-Truths: a dataset of about 1.5 million images for the targeted evaluation of AI-generated images. https://t.co/qJNzfm4zFs
Presenting the all-woman team behind Semi-Truths (+ @PoloChau 😁), landed in #NeurIPS2024!!
📍Come see us tomorrow at 11am - 2pm, West Ballroom A-D #5211.
Introducing ClickDiffusion!
We developed a system for precise image manipulation and generation that combines natural language instructions with visual feedback provided by the user through a direct manipulation interface.
🎉Thanks for the huge interest from the community in my last post comparing GPT-4o with UniTable for table recognition! We are excited to release more qualitative results of our UniTable!!! 😀
See more examples including paper and code in the thread 🧵(1/n)
Looking to safeguard your LLMs from deception?
🛡️LLM Self Defense is
🛠️Simple: No fine-tuning or preprocessing
🌐Generalizable: Works for GPT3.5 and Llama
💪Effective: Countering almost all attacks
Visit us at ICLR'24 tomorrow at Hall B #294 from 4:30pm - 6:30pm to know more!
I’m honored to be awarded with the Marshall D. Williamson Fellowship for academic excellence and leadership by @gtcomputing 🌟
Thank you @PoloChau for your unwavering support and encouragement!
🤔 Want to Fine-Tune LLMs with Your Private Data for FREE? 3-in-1 tutorial designed for everyone!
📖 Accessible blog post https://t.co/3kNIU8Hu4S
+ 💻 Step-by-step Colab notebook https://t.co/c0vR6lTZwB
+ 🎙️ High-level presentation
Thrilled to be donning the cap and gown for my Master's graduation today! 🚀🎓
I learned so many lessons at GT, both inside and outside the classrooms, that I will carry with me for the rest of my life. Thanks to everyone who supported me in this journey!
Go Jackets! 🐝
Several CSE students, faculty, and alumni were recognized last week at @gtcomputing's 33rd Annual Awards Celebration!
Stay tuned for our award wrap-up story to publish soon! Until then, here are a few highlights from the banquet! Congratulations, everyone! 🥳🎉
🎓 How to choose a PhD advisor? 💡My top tip: prioritize human qualities. Without the right people, research is not going to happen. 🌟Dive deeper here: https://t.co/P0tnzCILxY
📢 Georgia Tech's School of Computational Science and Engineering has multiple faculty openings! https://t.co/w6v6KwN07z
Join us at the coolest CSE department in the world! @GTCSE@gtcomputing@mlatgt
🛡️ Want to protect your AI models from attacks? You only need 3 robust principles! 🏆 #1 on RobustBench CIFAR-10 leaderboard
🔬 Robust Principles unlock the power of architectural robustness of models, datasets, adversarial training, and network designs! https://t.co/QXl1ZiTbkm
@ShripadBhat7 Fundamental and essential matrices are important in the epipolar geometry of stereo images. Both relate a point in one camera to a point in the other given rotation and translation. Essential matrix has 5 dof and fundamemtal matrix has 7 dof as it contains info about calibration
@ShripadBhat7 GMM is used to identify objects by classifying them in gaussian distributions. There are 2 stages in the model creation: expectation and maximization. In maximization we adjust the mean variance and weight of the distributions to maximize the possibility of correct classification