2 papers
cs.LG2026
Toward Efficient Uncertainty in LLMs through Evidential Knowledge Distillation
Lakshmana Sri Harsha Nemani, P. K. Srijith, Tomasz KuÅmierczyk
Accurate uncertainty quantification remains a key challenge for standard LLMs, prompting the adoption of Bayesian and ensemble-based methods. However, such methods typically necess…
cs.LG2024
Linked Adapters: Linking Past and Future to Present for Effective Continual Learning
Dupati Srikar Chandra, P. K. Srijith, Dana Rezazadegan +1
Continual learning allows the system to learn and adapt to new tasks while retaining the knowledge acquired from previous tasks. However, deep learning models suffer from catastrop…