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20242026
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cs.CL2026

KisMATH: Do LLMs Have Knowledge of Implicit Structures in Mathematical Reasoning?

Soumadeep Saha, Akshay Chaturvedi, Saptarshi Saha +2

Chain-of-thought (CoT) traces have been shown to improve performance of large language models on a plethora of reasoning tasks, yet there is no consensus on the mechanism by which…

cs.CL2025

sudoLLM: On Multi-role Alignment of Language Models

Soumadeep Saha, Akshay Chaturvedi, Joy Mahapatra +1

User authorization-based access privileges are a key feature in many safety-critical systems, but have not been extensively studied in the large language model (LLM) realm. In this…

cs.CL2025

Factual Inconsistency in Data-to-Text Generation Scales Exponentially with LLM Size: A Statistical Validation

Joy Mahapatra, Soumyajit Roy, Utpal Garain

Monitoring factual inconsistency is essential for ensuring trustworthiness in data-to-text generation (D2T). While large language models (LLMs) have demonstrated exceptional perfor…

cs.CL2024

An Extensive Evaluation of Factual Consistency in Large Language Models for Data-to-Text Generation

Joy Mahapatra, Utpal Garain

Large Language Models (LLMs) have shown exceptional performance across various Data-to-Text Generation (DTG) tasks. However, generating factually consistent text in DTG remains cha…

cs.CL2024

Impact of Model Size on Fine-tuned LLM Performance in Data-to-Text Generation: A State-of-the-Art Investigation

Joy Mahapatra, Utpal Garain

Data-to-text (D2T) generation aims to generate human-readable text from semi-structured data, such as tables and graphs. The recent success of D2T is largely attributed to advancem…