3 citations · 5 across the 4 of their papers we have counts for
4 papers
CurLL: A Developmental Framework to Evaluate Continual Learning in Language Models
Pavan Kalyan, Shubhra Mishra, Satya Lokam +1
We introduce a comprehensive continual learning dataset and benchmark (CurlL) grounded in human developmental trajectories from ages 5-10, enabling systematic and fine-grained asse…
Exploring Continual Fine-Tuning for Enhancing Language Ability in Large Language Model
Divyanshu Aggarwal, Sankarshan Damle, Navin Goyal +2
A common challenge towards the adaptability of Large Language Models (LLMs) is their ability to learn new languages over time without hampering the model's performance on languages…
InversionView: A General-Purpose Method for Reading Information from Neural Activations
Xinting Huang, Madhur Panwar, Navin Goyal +1
The inner workings of neural networks can be better understood if we can fully decipher the information encoded in neural activations. In this paper, we argue that this information…
Learning Syntax Without Planting Trees: Understanding Hierarchical Generalization in Transformers
Kabir Ahuja, Vidhisha Balachandran, Madhur Panwar +4
Transformers trained on natural language data have been shown to learn its hierarchical structure and generalize to sentences with unseen syntactic structures without explicitly en…