5 papers
Emotion Entanglement and Bayesian Inference for Multi-Dimensional Emotion Understanding
Hemanth Kotaprolu, Kishan Maharaj, Raey Zhao +2
Understanding emotions in natural language is inherently a multi-dimensional reasoning problem, where multiple affective signals interact through context, interpersonal relations,…
Beyond the Autoregressive Horizon: A Comprehensive Survey of Diffusion Models, World Modelling, and State Space Models for Code
Kishan Maharaj, Ashita Saxena, Srikanth Tamilselvam
Autoregressive (AR) language models have driven significant progress in automated software engineering, enabling powerful code generation and assistance systems. However, the next-…
Robustness and Reasoning Fidelity of Large Language Models in Long-Context Code Question Answering
Kishan Maharaj, Nandakishore Menon, Ashita Saxena +1
Large language models (LLMs) increasingly assist software engineering tasks that require reasoning over long code contexts, yet their robustness under varying input conditions rema…
ETF: An Entity Tracing Framework for Hallucination Detection in Code Summaries
Kishan Maharaj, Vitobha Munigala, Srikanth G. Tamilselvam +5
Recent advancements in large language models (LLMs) have significantly enhanced their ability to understand both natural language and code, driving their use in tasks like natural…
Understand the Implication: Learning to Think for Pragmatic Understanding
Settaluri Lakshmi Sravanthi, Kishan Maharaj, Sravani Gunnu +2
Pragmatics, the ability to infer meaning beyond literal interpretation, is crucial for social cognition and communication. While LLMs have been benchmarked for their pragmatic unde…