Priyanshu Gupta — accepted AI-conference papers

2024

MetaReflection: Learning Instructions for Language Agents using Past Reflections

Priyanshu Gupta, Shashank Kirtania, Ananya Singha, Sumit Gulwani, Arjun Radhakrishna, Gustavo Soares +1

EMNLP 2024main

The popularity of Large Language Models (LLMs) have unleashed a new age of Language Agents for solving a diverse range of tasks. While contemporary frontier LLMs are capable enough to power reasonably good Language agents, the closed-API model makes it hard to improve in cases they perform sub-optim…

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2023

TSTR: Target Similarity Tuning Meets the Real World

Anirudh Khatry, Sumit Gulwani, Priyanshu Gupta, Vu Le, Mukul Singh, Ananya Singha +1

EMNLP 2023short findings

Target similarity tuning (TST) is a method of selecting relevant examples in natural language (NL) to code generation through large language models (LLMs) to improve performance. Its goal is to adapt a sentence embedding model to have the similarity between two NL inputs match the similarity between…

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