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cs.LG2026
On the Identifiability of Controlled World Models
Xiangteng Zhang, Yang Guan, Bo Zhang +3
World model serves as a promising tool to infer environment dynamics under high-dimensional observations and candidate actions. Recently, LeCun's JEPA provides a compelling framewo…
cs.LG2025
Differentially Private In-context Learning via Sampling Few-shot Mixed with Zero-shot Outputs
James Flemings, Haosheng Gan, Hongyi Li +2
In-context learning (ICL) has shown promising improvement in downstream task adaptation of LLMs by augmenting prompts with relevant input-output examples (demonstrations). However,…