7 papers
Code-Guided Reasoning for Small Language Models: Evaluating Executable MCQA Scaffolds
Prateek Biswas, Dhaval Patel, Vedant Khandelwal +2
Multiple-choice QA benchmarks usually evaluate small language models (SLMs) as direct answerers, but deployed language-model systems increasingly rely on external scaffolds such as…
SAAG: Structured Agent Assessment and Grounding
Ritvik Garimella, Vedant Khandelwal, Anvi Kohli +1
Exact-match evaluation of agent-calling obscures qualitatively different failure modes: a model may select the right function yet hallucinate argument values, or satisfy a schema w…
A Neurosymbolic Fast and Slow Architecture for Graph Coloring
Vedant Khandelwal, Vishal Pallagani, Biplav Srivastava +1
Constraint Satisfaction Problems (CSPs) present significant challenges to artificial intelligence due to their intricate constraints and the necessity for precise solutions. Existi…
Language Models Coupled with Metacognition Can Outperform Reasoning Models
Vedant Khandelwal, Francesca Rossi, Keerthiram Murugesan +4
Large language models (LLMs) excel in speed and adaptability across various reasoning tasks, but they often struggle when strict logic or constraint enforcement is required. In con…
NeuroLit Navigator: A Neurosymbolic Approach to Scholarly Article Searches for Systematic Reviews
Vedant Khandelwal, Kaushik Roy, Valerie Lookingbill +4
The introduction of Large Language Models (LLMs) has significantly impacted various fields, including education, for example, by enabling the creation of personalized learning mate…
PDDLFuse: A Tool for Generating Diverse Planning Domains
Vedant Khandelwal, Amit Sheth, Forest Agostinelli
Various real-world challenges require planning algorithms that can adapt to a broad range of domains. Traditionally, the creation of planning domains has relied heavily on human im…