Venue: SIT001 Abstract: Large Language Models (LLMs) demonstrate strong general reasoning ability, yet still suffer from hallucination, limited faithfulness, and a lack of interpretability—especially in knowledge-intensive or domain-specific settings. Knowledge Graphs (KGs), on the other hand, provide structured, explicit, and verifiable representations of facts, but are incomplete and lack linguistic flexibility. This talk presents recent… Read More »Unifying Large Language Models and Knowledge Graphs for Faithful and Interpretable Reasoning by Gholamreza (Reza) Haffari

Venue: Bharti501 Abstract: Pretrained transformers readily adapt to new sequence modeling tasks via zero-shot prompting, but relational domains still lack architectures that transfer across datasets and tasks. The core challenge is the diversity of relational data, with varying heterogeneous schemas, graph structures and functional dependencies. In this talk, I will present the Relational Transformer (RT) architecture,… Read More »Relational Transformer: Toward Zero-Shot Foundation Models for Relational Data by Rishabh Ranjan

Venue: Bharti 501 Abstract: Suppose Alice uses a t-out-of-n secret sharing to store her secret key on n servers. Her secret key is protected as long as t of them do not collude. However, what if a less-than-t subset of the servers decides to offer the shares they have for sale? In this case, Alice… Read More »Traceable Secret Sharing: Strong Security and Efficient Constructions by Aditi Partap

Venue: Bharti501 Abstract: We study the online busy time scheduling model on heterogeneous machines. In our setting, jobs with uniform length arrive online with a deadline that becomes known to the algorithm at the job's arrival time. An algorithm has access to machines, each with different associated capacities and costs. The goal is to schedule… Read More »Online Flexible Busy Time Scheduling on Heterogeneous Machines by Gruia Calinescu

Venue: Bharti-501/MS Teams Abstract: The goal of error correcting codes is to encode data in a way that allows for this data to be recovered even if the encoded copy is corrupted by an adversary. The usual algorithmic challenge associated with codes, called decoding, is to output the uncorrupted copy of data by looking only at… Read More »Coping with choices – List Decoding in Coding Theory by Dr. Shashank Srivastava

Venue: SIT001 Abstract:  The vast expansion of online information has shifted the challenge from simply locating data to efficiently filtering and aggregating relevant content from diverse sources. This talk introduces innovative methodologies aimed at enhancing automated information seeking capabilities within intelligent systems. I will present a modular, agent-based framework that decomposes the information-seeking process into navigation,… Read More »Agentic Information Seeking for Knowledge Acquisition by Revanth Reddy

Venue: SIT113 Abstract: The Android operating system uses a permission framework that allows users to control access to their private data, such as location and contacts, when using apps. However, many apps become non-functional or crash if denied these permissions, effectively pressuring users to grant access and compromising their privacy. In this paper, we introduce WhiteLie,… Read More »WhiteLie: A Robust System for Spoofing User Data in Android Platforms by Harish Yadav