6 papers
ARREST: Adversarial Resilient Regulation Enhancing Safety and Truth in Large Language Models
Sharanya Dasgupta, Arkaprabha Basu, Sujoy Nath +1
Human cognition, driven by complex neurochemical processes, oscillates between imagination and reality and learns to self-correct whenever such subtle drifts lead to hallucinations…
HalluShift++: Bridging Language and Vision through Internal Representation Shifts for Hierarchical Hallucinations in MLLMs
Sujoy Nath, Arkaprabha Basu, Sharanya Dasgupta +1
Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in vision-language understanding tasks. While these models often produce linguistically coherent…
Relation-Aware Slicing in Cross-Domain Alignment
Dhruv Sarkar, Aprameyo Chakrabartty, Anish Chakrabarty +1
The Sliced Gromov-Wasserstein (SGW) distance, aiming to relieve the computational cost of solving a non-convex quadratic program that is the Gromov-Wasserstein distance, utilizes p…
On the Existence of Universal Simulators of Attention
Debanjan Dutta, Anish Chakrabarty, Faizanuddin Ansari +1
Previous work on the learnability of transformers \textemdash\ focused primarily on examining their ability to approximate specific algorithmic patterns through training \textemdas…
HalluShift: Measuring Distribution Shifts towards Hallucination Detection in LLMs
Sharanya Dasgupta, Sujoy Nath, Arkaprabha Basu +2
Large Language Models (LLMs) have recently garnered widespread attention due to their adeptness at generating innovative responses to the given prompts across a multitude of domain…
On Robust Cross Domain Alignment
Anish Chakrabarty, Arkaprabha Basu, Swagatam Das
The Gromov-Wasserstein (GW) distance is an effective measure of alignment between distributions supported on distinct ambient spaces. Calculating essentially the mutual departure f…