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Found 12 papers, 3 papers with code
Multimodal Auto Validation For Self-Refinement in Web Agents
As our world digitizes, web agents that can automate complex and monotonous tasks are becoming essential in streamlining workflows.
SEAL: Suite for Evaluating API-use of LLMs
Large language models (LLMs) have limitations in handling tasks that require real-time access to external APIs.
MathViz-E: A Case-study in Domain-Specialized Tool-Using Agents
There has been significant recent interest in harnessing LLMs to control software systems through multi-step reasoning, planning and tool-usage.
Building a Domain-specific Guardrail Model in Production
Generative AI holds the promise of enabling a range of sought-after capabilities and revolutionizing workflows in various consumer and enterprise verticals.
Agent-E: From Autonomous Web Navigation to Foundational Design Principles in Agentic Systems
AI Agents are changing the way work gets done, both in consumer and enterprise domains.
Better RAG using Relevant Information Gain
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 context window.
Automating question generation from educational text
The use of question-based activities (QBAs) is wide-spread in education, traditionally forming an integral part of the learning and assessment process.
Voice Privacy with Smart Digital Assistants in Educational Settings
We evaluate the ASR performance of the conversion in terms of word error rate and show the promise of this framework in preserving the content of the input speech.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Content Customization for Micro Learning using Human Augmented AI Techniques
Also, manual video curation by educators is a highly labor-intensive process.
Design and Evaluation of a Tutor Platform for Personalized Vocabulary Learning
A pilot study with 180 kindergarten learners allowed the tutor to collect various kinds of activity information suitable for insights and interventions both at an individual- and class-level.
Human-Machine Inference Networks For Smart Decision Making: Opportunities and Challenges
The emerging paradigm of Human-Machine Inference Networks (HuMaINs) combines complementary cognitive strengths of humans and machines in an intelligent manner to tackle various inference tasks and achieves higher performance than either humans or machines by themselves.
Multi-object Classification via Crowdsourcing with a Reject Option
We present an aggregation approach using a weighted majority voting rule, where each worker's response is assigned an optimized weight to maximize the crowd's classification performance.
