activity
20242026
most citedAgent-E: From Autonomous Web Navigation to Foundational Design Principles in Agentic Systems

2 citations · 5 across the 7 of their papers we have counts for

collaborators

10 papers

cs.SE2026

Beyond Type-checking: Towards Holistic Evaluation of Formal Specification Generation

Srijith Nair, Aditya Vempaty, Jia Liu +1

When generating verifiable code, natural language requirements are mapped to machine checked code using LLMs and agentic workflows. A crucial component of this pipeline is specific…

cs.SE2026

Eliciting Specifications: When Does Interactive Clarification Help?

Mowafak Allaham, Aditya Vempaty, Ashish Jagmohan +2

LLMs can generate Lean specifications from task descriptions, but those descriptions are often underspecified or ambiguous and may omit verifier-relevant edge cases, yielding imper…

cs.AI2026

Second-Order Problem Solving for Recursive Self-Improvement in Formal Verification

Yuxuan Jiang, Aditya Vempaty, Ashish Jagmohan

Recursive self-improvement (RSI) enables agents to iteratively optimize their workflows via execution feedback. However, standard RSI typically operates as a first-order optimizer:…

cs.AI2025

Reflection-Based Memory For Web navigation Agents

Ruhana Azam, Aditya Vempaty, Ashish Jagmohan

Web navigation agents have made significant progress, yet current systems operate with no memory of past experiences -- leading to repeated mistakes and an inability to learn from…

cs.AI2025

Learning API Functionality from In-Context Demonstrations for Tool-based Agents

Bhrij Patel, Ashish Jagmohan, Aditya Vempaty

Digital tool-based agents, powered by Large Language Models (LLMs), that invoke external Application Programming Interfaces (APIs) often rely on documentation to understand API fun…

cs.AI2024

Multimodal Auto Validation For Self-Refinement in Web Agents

Ruhana Azam, Tamer Abuelsaad, Aditya Vempaty +1

As our world digitizes, web agents that can automate complex and monotonous tasks are becoming essential in streamlining workflows. This paper introduces an approach to improving w…

cs.AI2024

SEAL: Suite for Evaluating API-use of LLMs

Woojeong Kim, Ashish Jagmohan, Aditya Vempaty

Large language models (LLMs) have limitations in handling tasks that require real-time access to external APIs. While several benchmarks like ToolBench and APIGen have been develop…

cs.CY2024★ 2 cited

Building a Domain-specific Guardrail Model in Production

Mohammad Niknazar, Paul V Haley, Latha Ramanan +12

Generative AI holds the promise of enabling a range of sought-after capabilities and revolutionizing workflows in various consumer and enterprise verticals. However, putting a mode…

cs.SE2024★ 1 cited

MathViz-E: A Case-study in Domain-Specialized Tool-Using Agents

Arya Bulusu, Brandon Man, Ashish Jagmohan +3

There has been significant recent interest in harnessing LLMs to control software systems through multi-step reasoning, planning and tool-usage. While some promising results have b…

cs.AI2024★ 2 cited

Agent-E: From Autonomous Web Navigation to Foundational Design Principles in Agentic Systems

Tamer Abuelsaad, Deepak Akkil, Prasenjit Dey +3

AI Agents are changing the way work gets done, both in consumer and enterprise domains. However, the design patterns and architectures to build highly capable agents or multi-agent…