3 papers
cs.AI2026
When Should LLMs Be Less Specific? Selective Abstraction for Reliable Long-Form Text Generation
Shani Goren, Ido Galil, Ran El-Yaniv
LLMs are widely used, yet they remain prone to factual errors that erode user trust and limit adoption in high-risk settings. One approach to mitigate this risk is to equip models…
cs.CL2025
ChaI-TeA: A Benchmark for Evaluating Autocompletion of Interactions with LLM-based Chatbots
Shani Goren, Oren Kalinsky, Tomer Stav +6
The rise of LLMs has deflected a growing portion of human-computer interactions towards LLM-based chatbots. The remarkable abilities of these models allow users to interact using l…
cs.LG2025
Hierarchical Selective Classification
Shani Goren, Ido Galil, Ran El-Yaniv
Deploying deep neural networks for risk-sensitive tasks necessitates an uncertainty estimation mechanism. This paper introduces hierarchical selective classification, extending sel…