3 papers
cs.AI2025
Synthesizing Procedural Memory: Challenges and Architectures in Automated Workflow Generation
Nishant Gaurav, Adit Akarsh, Ankit Ranjan +1
While CodeMem establishes executable code as the optimal representation for agentic procedural memory, the mechanism for autonomously synthesizing this memory from a blank slate re…
cs.SE2025
CodeMem: Architecting Reproducible Agents via Dynamic MCP and Procedural Memory
Nishant Gaurav, Adit Akarsh, Tejas Ravishankar +1
Current tool-using AI agents suffer from limited action space, context inefficiency, and probabilistic instability that makes them unsuitable for handling repetitive tasks which ar…
cs.SE2025
Dynamic ReAct: Scalable Tool Selection for Large-Scale MCP Environments
Nishant Gaurav, Adit Akarsh, Ankit Ranjan +1
We present Dynamic ReAct, a novel approach for enabling ReAct agents to efficiently operate with extensive Model Control Protocol (MCP) tool sets that exceed the contextual memory…