2 citations · 8 across the 12 of their papers we have counts for
16 papers
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…
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…
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:…
Emergence World: Adversarial Stress-Testing of Long-Horizon Multi-Agent Systems
Deepak Akkil, Tamer Abuelsaad, Karthik Vikram +5
As AI agents move from bounded tasks to persistent deployments, failures can propagate through memory, tools, other agents, and environmental state long after their interactions. T…
Emergence World: A Platform for Evaluating Long-Horizon Multi-Agent Autonomy
Deepak Akkil, Ravi Kokku, Karthik Vikram +3
Most evaluations of LLM agents look like exams: a discrete task, a clean environment, a score in minutes or hours. We argue that this approach is mismatched with the deployment con…
Introducing Spotlight: A Novel Approach for Generating Captivating Key Information from Documents
Ankan Mullick, Sombit Bose, Rounak Saha +6
In this paper, we introduce Spotlight, a novel paradigm for information extraction that produces concise, engaging narratives by highlighting the most compelling aspects of a docum…
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…
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…
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…
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…
Leveraging the Power of LLMs: A Fine-Tuning Approach for High-Quality Aspect-Based Summarization
Ankan Mullick, Sombit Bose, Rounak Saha +6
The ever-increasing volume of digital information necessitates efficient methods for users to extract key insights from lengthy documents. Aspect-based summarization offers a targe…
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…
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…
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…
Better RAG using Relevant Information Gain
Marc Pickett, Jeremy Hartman, Ayan Kumar Bhowmick +2
A common way to extend the memory of large language models (LLMs) is by retrieval augmented generation (RAG), which inserts text retrieved from a larger memory into an LLM's contex…
Automating question generation from educational text
Ayan Kumar Bhowmick, Ashish Jagmohan, Aditya Vempaty +5
The use of question-based activities (QBAs) is wide-spread in education, traditionally forming an integral part of the learning and assessment process. In this paper, we design and…