84 citations · 97 across the 7 of their papers we have counts for
8 papers
Granite-Function Calling Model: Introducing Function Calling Abilities via Multi-task Learning of Granular Tasks
Ibrahim Abdelaziz, Kinjal Basu, Mayank Agarwal +23
Large language models (LLMs) have recently shown tremendous promise in serving as the backbone to agentic systems, as demonstrated by their performance in multi-faceted, challengin…
An Approach to Build Zero-Shot Slot-Filling System for Industry-Grade Conversational Assistants
G P Shrivatsa Bhargav, Sumit Neelam, Udit Sharma +10
We present an approach to build Large Language Model (LLM) based slot-filling system to perform Dialogue State Tracking in conversational assistants serving across a wide variety o…
An Ensemble Approach for Automated Theorem Proving Based on Efficient Name Invariant Graph Neural Representations
Achille Fokoue, Ibrahim Abdelaziz, Maxwell Crouse +5
Using reinforcement learning for automated theorem proving has recently received much attention. Current approaches use representations of logical statements that often rely on the…
Targeted Extraction of Temporal Facts from Textual Resources for Improved Temporal Question Answering over Knowledge Bases
Nithish Kannen, Udit Sharma, Sumit Neelam +4
Knowledge Base Question Answering (KBQA) systems have the goal of answering complex natural language questions by reasoning over relevant facts retrieved from Knowledge Bases (KB).…
A Benchmark for Generalizable and Interpretable Temporal Question Answering over Knowledge Bases
Sumit Neelam, Udit Sharma, Hima Karanam +22
Knowledge Base Question Answering (KBQA) tasks that involve complex reasoning are emerging as an important research direction. However, most existing KBQA datasets focus primarily…
SYGMA: System for Generalizable Modular Question Answering OverKnowledge Bases
Sumit Neelam, Udit Sharma, Hima Karanam +21
Knowledge Base Question Answering (KBQA) tasks that in-volve complex reasoning are emerging as an important re-search direction. However, most KBQA systems struggle withgeneralizab…
Learning to Guide a Saturation-Based Theorem Prover
Ibrahim Abdelaziz, Maxwell Crouse, Bassem Makni +8
Traditional automated theorem provers have relied on manually tuned heuristics to guide how they perform proof search. Recently, however, there has been a surge of interest in the…
Logical Neural Networks
Ryan Riegel, Alexander Gray, Francois Luus +12
We propose a novel framework seamlessly providing key properties of both neural nets (learning) and symbolic logic (knowledge and reasoning). Every neuron has a meaning as a compon…