most citedGranite Code Models: A Family of Open Foundation Models for Code Intelligence

10 citations · 10 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CL2025

Chatty-KG: A Multi-Agent AI System for On-Demand Conversational Question Answering over Knowledge Graphs

Reham Omar, Abdelghny Orogat, Ibrahim Abdelaziz +3

Conversational Question Answering over Knowledge Graphs (KGs) combines the factual grounding of KG-based QA with the interactive nature of dialogue systems. KGs are widely used in…

cs.CL2025

ToolRM: Outcome Reward Models for Tool-Calling Large Language Models

Mayank Agarwal, Ibrahim Abdelaziz, Kinjal Basu +4

As large language models (LLMs) increasingly interact with external tools, reward modeling for tool use has emerged as a critical yet underexplored area of research. Existing rewar…

cs.SE2025

LongFuncEval: Measuring the effectiveness of long context models for function calling

Kiran Kate, Tejaswini Pedapati, Kinjal Basu +5

Multiple recent studies have documented large language models' (LLMs) performance on calling external tools/functions. Others focused on LLMs' abilities to handle longer context le…

cs.AI2025

R2D2: Remembering, Replaying and Dynamic Decision Making with a Reflective Agentic Memory

Tenghao Huang, Kinjal Basu, Ibrahim Abdelaziz +3

The proliferation of web agents necessitates advanced navigation and interaction strategies within complex web environments. Current models often struggle with efficient navigation…

cs.AI202410 cited

Granite Code Models: A Family of Open Foundation Models for Code Intelligence

Mayank Mishra, Matt Stallone, Gaoyuan Zhang +43

Large Language Models (LLMs) trained on code are revolutionizing the software development process. Increasingly, code LLMs are being integrated into software development environmen…