3.1k citations · 3.1k across the 14 of their papers we have counts for
15 papers
Adversarial Arena: Crowdsourcing Data Generation through Interactive Competition
Prasoon Goyal, Sattvik Sahai, Michael Johnston +14
Post-training Large Language Models requires diverse, high-quality data which is rare and costly to obtain, especially in low resource domains and for multi-turn conversations. Com…
Addressing LLM Diversity by Infusing Random Concepts
Pulin Agrawal, Prasoon Goyal
Large language models (LLMs) are known to produce outputs with limited diversity. In this work, we study whether infusing random concepts in the prompts can improve the diversity o…
From Narrow Unlearning to Emergent Misalignment: Causes, Consequences, and Containment in LLMs
Erum Mushtaq, Anil Ramakrishna, Satyapriya Krishna +5
Recent work has shown that fine-tuning on insecure code data can trigger an emergent misalignment (EMA) phenomenon, where models generate malicious responses even to prompts unrela…
Amazon Nova AI Challenge -- Trusted AI: Advancing secure, AI-assisted software development
Sattvik Sahai, Prasoon Goyal, Michael Johnston +13
AI systems for software development are rapidly gaining prominence, yet significant challenges remain in ensuring their safety. To address this, Amazon launched the Trusted AI trac…
Is the House Ready For Sleeptime? Generating and Evaluating Situational Queries for Embodied Question Answering
Vishnu Sashank Dorbala, Prasoon Goyal, Robinson Piramuthu +3
We present and tackle the problem of Embodied Question Answering (EQA) with Situational Queries (S-EQA) in a household environment. Unlike prior EQA work tackling simple queries th…
"Don't forget to put the milk back!" Dataset for Enabling Embodied Agents to Detect Anomalous Situations
James F. Mullen, Prasoon Goyal, Robinson Piramuthu +3
Home robots intend to make their users lives easier. Our work assists in this goal by enabling robots to inform their users of dangerous or unsanitary anomalies in their home. Some…