3 papers
cs.CL2026
Heterogeneity in Formal Linguistic Competence of Language Models: Is Data the Real Bottleneck?
H S V N S Kowndinya Renduchintala, Sumit Bhatia
Large Language Models (LLMs) exhibit a puzzling disparity in their formal linguistic competence: while they learn some linguistic phenomena with near-perfect mastery, they often pe…
cs.CL2024
POSIX: A Prompt Sensitivity Index For Large Language Models
Anwoy Chatterjee, H S V N S Kowndinya Renduchintala, Sumit Bhatia +1
Despite their remarkable capabilities, Large Language Models (LLMs) are found to be surprisingly sensitive to minor variations in prompts, often generating significantly divergent…
cs.CL2024
SMART: Submodular Data Mixture Strategy for Instruction Tuning
H S V N S Kowndinya Renduchintala, Sumit Bhatia, Ganesh Ramakrishnan
Instruction Tuning involves finetuning a language model on a collection of instruction-formatted datasets in order to enhance the generalizability of the model to unseen tasks. Stu…