168 citations · 646 across the 40 of their papers we have counts for
4 papers · 1 filter
EchoPrompt: Instructing the Model to Rephrase Queries for Improved In-context Learning
Rajasekhar Reddy Mekala, Yasaman Razeghi, Sameer Singh
Language models are achieving impressive performance on various tasks by aggressively adopting inference-time prompting techniques, such as zero-shot and few-shot prompting. In thi…
The Bias Amplification Paradox in Text-to-Image Generation
Preethi Seshadri, Sameer Singh, Yanai Elazar
Bias amplification is a phenomenon in which models exacerbate biases or stereotypes present in the training data. In this paper, we study bias amplification in the text-to-image do…
Selective Perception: Optimizing State Descriptions with Reinforcement Learning for Language Model Actors
Kolby Nottingham, Yasaman Razeghi, Kyungmin Kim +4
Large language models (LLMs) are being applied as actors for sequential decision making tasks in domains such as robotics and games, utilizing their general world knowledge and pla…
MISGENDERED: Limits of Large Language Models in Understanding Pronouns
Tamanna Hossain, Sunipa Dev, Sameer Singh
Content Warning: This paper contains examples of misgendering and erasure that could be offensive and potentially triggering. Gender bias in language technologies has been widely s…