2 papers
cs.CL2025
Reasoning Under Uncertainty: Exploring Probabilistic Reasoning Capabilities of LLMs
Mobina Pournemat, Keivan Rezaei, Gaurang Sriramanan +5
Despite widespread success in language understanding and generation, large language models (LLMs) exhibit unclear and often inconsistent behavior when faced with tasks that require…
cs.LG2025
A Unified Knowledge-Distillation and Semi-Supervised Learning Framework to Improve Industrial Ads Delivery Systems
Hamid Eghbalzadeh, Yang Wang, Rui Li +9
Industrial ads ranking systems conventionally rely on labeled impression data, which leads to challenges such as overfitting, slower incremental gain from model scaling, and biases…