2 citations · 8 across the 12 of their papers we have counts for
7 papers · 1 filter
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…