5 papers
HORIZON: A Benchmark for In-the-wild User Behaviour Modeling
Arnav Goel, Pranjal A Chitale, Bhawna Paliwal +2
User behavior in the real world is diverse, cross-domain, and spans long time horizons. Existing user modeling benchmarks however remain narrow, focusing mainly on short sessions a…
Router-Suggest: Dynamic Routing for Multimodal Auto-Completion in Visually-Grounded Dialogs
Sandeep Mishra, Devichand Budagam, Anubhab Mandal +3
Real-time multimodal auto-completion is essential for digital assistants, chatbots, design tools, and healthcare consultations, where user inputs rely on shared visual context. We…
Evaluating the Effectiveness and Scalability of LLM-Based Data Augmentation for Retrieval
Pranjal A. Chitale, Bishal Santra, Yashoteja Prabhu +1
Compact dual-encoder models are widely used for retrieval owing to their efficiency and scalability. However, such models often underperform compared to their Large Language Model…
SCULPT: Systematic Tuning of Long Prompts
Shanu Kumar, Akhila Yesantarao Venkata, Shubhanshu Khandelwal +3
Prompt optimization is essential for effective utilization of large language models (LLMs) across diverse tasks. While existing optimization methods are effective in optimizing sho…
Chat-Ghosting: A Comparative Study of Methods for Auto-Completion in Dialog Systems
Sandeep Mishra, Anubhab Mandal, Bishal Santra +3
Ghosting, the ability to predict a user's intended text input for inline query auto-completion, is an invaluable feature for modern search engines and chat interfaces, greatly enha…