EvoAgent: An Evolvable Agent Framework with Skill Learning and Multi-Agent Delegation
arXiv:2604.20133v2 Announce Type: replace Abstract: This paper proposes EvoAgent – an evolvable large language model (LLM) agent framework that integrates…
Shared Lexical Task Representations Explain Behavioral Variability In LLMs
arXiv:2604.22027v1 Announce Type: cross Abstract: One of the most common complaints about large language models (LLMs) is their prompt sensitivity…
SOLAR-RL: Semi-Online Long-horizon Assignment Reinforcement Learning
arXiv:2604.22558v1 Announce Type: cross Abstract: As Multimodal Large Language Models (MLLMs) mature, GUI agents are evolving from static interactions to…
Pre-trained Large Language Models Learn Hidden Markov Models In-context
arXiv:2506.07298v3 Announce Type: replace-cross Abstract: Hidden Markov Models (HMMs) are foundational tools for modeling sequential data with latent Markovian structure,…
Unlocking the Edge deployment and ondevice acceleration of multi-LoRA enabled one-for-all foundational LLM
arXiv:2604.18655v2 Announce Type: replace-cross Abstract: Deploying large language models (LLMs) on smartphones poses significant engineering challenges due to stringent constraints…
VLAA-GUI: Knowing When to Stop, Recover, and Search, A Modular Framework for GUI Automation
arXiv:2604.21375v2 Announce Type: replace-cross Abstract: Autonomous GUI agents face two fundamental challenges: early stopping, where agents prematurely declare success without…
Causal Concept Graphs in LLM Latent Space for Stepwise Reasoning
arXiv:2603.10377v2 Announce Type: replace-cross Abstract: Sparse autoencoders can localize where concepts live in language models, but not how they interact…
Cross-Domain Offshore Wind Power Forecasting: Transfer Learning Through Meteorological Clusters
arXiv:2601.19674v2 Announce Type: replace-cross Abstract: Ambitious decarbonisation targets are rapidly increasing the commission of new offshore wind farms. For these…
Hidden Failure Modes of Gradient Modification under Adam in Continual Learning, and Adaptive Decoupled Moment Routing as a Repair
arXiv:2604.22407v1 Announce Type: cross Abstract: Many continual-learning methods modify gradients upstream (e.g., projection, penalty rescaling, replay mixing) while treating Adam…
AdaptEvolve: Improving Efficiency of Evolutionary AI Agents through Adaptive Model Selection
arXiv:2602.11931v2 Announce Type: replace-cross Abstract: Evolutionary agentic systems intensify the trade-off between computational efficiency and reasoning capability by repeatedly invoking…