2 citations · 4 across the 9 of their papers we have counts for
4 papers · 1 filter
Scaling Competence, Shrinking Reasoning: Cognitive Signatures in Language Model Learning
Mukul Singh, Ananya Singha, Arjun Radhakrishna +1
We analyze reasoning in language models during task-specific fine-tuning and draws parallel between reasoning tokens--intermediate steps generated while solving problem and the hum…
Ordered Semantically Diverse Sampling for Textual Data
Ashish Tiwari, Mukul Singh, Ananya Singha +1
The goal of diversity sampling is to select a representative subset of data in a way that maximizes information contained in the subset while keeping its cardinality small. We intr…
MetaReflection: Learning Instructions for Language Agents using Past Reflections
Priyanshu Gupta, Shashank Kirtania, Ananya Singha +4
The popularity of Large Language Models (LLMs) have unleashed a new age ofLanguage Agents for solving a diverse range of tasks. While contemporary frontier LLMs are capable enough…
Tabular Representation, Noisy Operators, and Impacts on Table Structure Understanding Tasks in LLMs
Ananya Singha, José Cambronero, Sumit Gulwani +2
Large language models (LLMs) are increasingly applied for tabular tasks using in-context learning. The prompt representation for a table may play a role in the LLMs ability to proc…