activity
20232026
most citedCombining Behaviors with the Successor Features Keyboard

1 citations · 1 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

On Safety Risks in Experience-Driven Self-Evolving Agents

Weixiang Zhao, Yichen Zhang, Yingshuo Wang +8

Experience-driven self-evolution has emerged as a promising paradigm for improving the autonomy of large language model agents, yet its reliance on self-curated experience introduc…

cs.CV2026

Enhancing Mixture-of-Experts Specialization via Cluster-Aware Upcycling

Sanghyeok Chu, Pyunghwan Ahn, Gwangmo Song +3

Sparse Upcycling provides an efficient way to initialize a Mixture-of-Experts (MoE) model from pretrained dense weights instead of training from scratch. However, since all experts…

cs.CL2026

EXAONE 4.5 Technical Report

Eunbi Choi, Kibong Choi, Sehyun Chun +55

This technical report introduces EXAONE 4.5, the first open-weight vision language model released by LG AI Research. EXAONE 4.5 is architected by integrating a dedicated visual enc…

cs.LG2025

Preemptive Solving of Future Problems: Multitask Preplay in Humans and Machines

Wilka Carvalho, Sam Hall-McMaster, Honglak Lee +1

Humans can pursue a near-infinite variety of tasks, but typically can only pursue a small number at the same time. We hypothesize that humans leverage experience on one task to pre…

cs.AI2023★ 1 cited

Combining Behaviors with the Successor Features Keyboard

Wilka Carvalho, Andre Saraiva, Angelos Filos +7

The Option Keyboard (OK) was recently proposed as a method for transferring behavioral knowledge across tasks. OK transfers knowledge by adaptively combining subsets of known behav…