3 papers
cs.CL2025
What Works for 'Lost-in-the-Middle' in LLMs? A Study on GM-Extract and Mitigations
Mihir Gupte, Eshan Dixit, Muhammad Tayyab +1
The diminishing ability of large language models (LLMs) to effectively utilize long-range context-the "lost-in-the-middle" phenomenon-poses a significant challenge in retrieval-bas…
cs.CL2025
Towards Autoformalization of LLM-generated Outputs for Requirement Verification
Mihir Gupte, Ramesh S
Autoformalization, the process of translating informal statements into formal logic, has gained renewed interest with the emergence of powerful Large Language Models (LLMs). While…
cs.CL2025
Is Implicit Knowledge Enough for LLMs? A RAG Approach for Tree-based Structures
Mihir Gupte, Paolo Giusto, Ramesh S
Large Language Models (LLMs) are adept at generating responses based on information within their context. While this ability is useful for interacting with structured data like cod…