Speaker: Dr. Manisha Luthra Agnihotri is the Deputy Head of the German Research Center for Artificial Intelligence (DFKI) in Darmstadt. It is an online talk. Please write to the CSE office to get the Teams link. Abstract: In this talk, I will outline my vision for next-generation, AI-enhanced data management systems through the lens of… Read More »Next-Generation AI-Enhanced Stream Processing
Speaker: Dr. Rima Hazra Abstract: In this talk, we explore cutting-edge strategies for enhancing the safety and ethical alignment of large language models (LLMs). The research spans various approaches, including red teaming and jailbreaking techniques, which assess and improve model robustness and ethical integrity. We delve into how instruction-centric responses, when generated by LLMs, can increase… Read More »Enhancing Safety and Ethical Alignment in Large Language Models by Rima Hazra
Title: Giving Some Space Can Be Hard: Two New Models to Match Agents with Locations Speaker: Shivika Narang (UNSW Sydney) Abstract: There can be a multitude of reasons to match agents to specific locations in a given space. In this talk, we cover two: distributing delivery orders and assigning office spaces. For both settings, we… Read More »Giving Some Space Can Be Hard: Two New Models to Match Agents with Locations by Shivika Narang
Speaker: Dr. Arun Balajee Vasudevan is currently a Research Scientist at Amazon Abstract: Autonomous robots have several potential applications such as virtual assistants, VR/AR, gaming, self-driving technologies, city planning and others. To achieve autonomy, a robot needs to see and hear the environment, before it can converse or navigate favorably to perform a human-desired task.… Read More »Multimodal Learning in 3D environments: Perception, and Simulation
Speaker: Dr. Anshu Yadav, Postdoctoral Researcher, Institute of Science and Technology, Austria Abstract: In today's world, the rapid advancement of technology has led to the generation of vast amounts of sensitive data, which must be accessed in a secure and controlled manner to facilitate research across various domains. Often this data, associated with a single… Read More »Designing advanced cryptographic primitives in distributed settings
Title: Thinking Geometrically in the World of Data-driven Models Abstract: As learning models grow in scale and capacity, a natural question arises: is it still relevant to think geometrically, or should we seek more data? In this talk, I will argue that geometry remains essential, not just for interpretability, but for enabling control, structure, and… Read More »Thinking Geometrically in the World of Data-driven Models by Niloy J. Mitra
Title: Dot-Product Proofs Speaker: Prahladh Harsha (TIFR Mumbai): Details: July 28 (Monday) | 11:30 AM | Bharti 404 Abstract: A dot-product proof is a simple probabilistic proof system in which the verifier decides whether to accept an input vector based on a single linear combination of the entries of the input and a proof vector. In this… Read More »Dot-Product Proofs by Prahladh Harsha
Abstract: Aggregating multiple input rankings over a set of candidates to generate a consensus ranking is one of the fundamental ranking problems, having many applications in social choice theory, hiring, college admission, web search, and databases. However, the optimal consensus ranking might be biased against any individual candidate or candidates belonging to certain marginalized communities… Read More »Rank Aggregation and Fairness by Diptarka Chakraborty
Title: Multiturn Evals (and RL) for LLMs Details: 8th August, 12 pm, SIT001 Abstract: LLMs often fail at multi-step tasks requiring memory and strategic planning, a gap not captured by traditional single-turn evals. To address this, we've developed a suite of human and automated evals that stress test Gemini on these capabilities. This talk will cover… Read More »Multiturn Evals (and RL) for LLMs by Kartikeya Badola
Title: Explainable AI for Malware Analysis Abstract: In recent years, explainable artificial intelligence (XAI) has become a critical component of ensuring transparency and trust in machine learning systems, particularly in high-stakes domains like cybersecurity. This talk will begin with a basic introduction to XAI, highlighting its importance in understanding model decisions, especially in the context of… Read More »Explainable AI for Malware Analysis by Mohd Saqib
