1 citations · 1 across the 13 of their papers we have counts for
18 papers
Beyond Accuracy: Diagnosing Algebraic Reasoning Failures in LLMs Across Nine Complexity Dimensions
Parth Patil, Dhruv Kumar, Yash Sinha +1
Algebraic reasoning remains one of the most informative stress tests for large language models, yet current benchmarks provide no mechanism for attributing failure to a specific ca…
Measuring Representation Robustness in Large Language Models for Geometry
Vedant Jawandhia, Yash Sinha, Murari Mandal +2
Large language models (LLMs) are increasingly evaluated on mathematical reasoning, yet their robustness to equivalent problem representations remains poorly understood. In geometry…
The Compliance Paradox: Semantic-Instruction Decoupling in Automated Academic Code Evaluation
Devanshu Sahoo, Manish Prasad, Vasudev Majhi +5
The rapid integration of Large Language Models (LLMs) into educational assessment rests on the unverified assumption that instruction following capability translates directly to ob…
When Reject Turns into Accept: Quantifying the Vulnerability of LLM-Based Scientific Reviewers to Indirect Prompt Injection
Devanshu Sahoo, Manish Prasad, Vasudev Majhi +5
Driven by surging submission volumes, scientific peer review has catalyzed two parallel trends: individual over-reliance on LLMs and institutional AI-powered assessment systems. Th…
NagaNLP: Bootstrapping NLP for Low-Resource Nagamese Creole with Human-in-the-Loop Synthetic Data
Agniva Maiti, Manya Pandey, Murari Mandal
The vast majority of the world's languages, particularly creoles like Nagamese, remain severely under-resourced in Natural Language Processing (NLP), creating a significant barrier…
How to Trick Your AI TA: A Systematic Study of Academic Jailbreaking in LLM Code Evaluation
Devanshu Sahoo, Vasudev Majhi, Arjun Neekhra +3
The use of Large Language Models (LLMs) as automatic judges for code evaluation is becoming increasingly prevalent in academic environments. But their reliability can be compromise…