Heavy-Tailed Memory Traces in Long-Horizon Language Agents
arXiv:2610.00010v1 Announce Type: new Abstract: Long-horizon language agents increasingly rely on external memory as a frozen world model, yet current…
arXiv:2610.00010v1 Announce Type: new Abstract: Long-horizon language agents increasingly rely on external memory as a frozen world model, yet current…
arXiv:2609.40253v2 Announce Type: replace-cross Abstract: Online training enables computer-use agents (CUAs) to improve through interaction with executable environments. However, existing…
arXiv:2610.01133v1 Announce Type: cross Abstract: Scaling reasoning typically spends more compute on reinforcement learning (RL) or on inference. We show…
arXiv:2610.01118v1 Announce Type: cross Abstract: A long-term conversational assistant must recall the right memory at the right moment, yet the…
arXiv:2609.39247v2 Announce Type: replace-cross Abstract: Standard language model RL algorithms credit every token of a long rollout with the same…
arXiv:2609.38282v1 Announce Type: new Abstract: Vision-language models may rewrite anomalous text in images into linguistically plausible expressions, compromising OCR transcription…
arXiv:2609.38036v2 Announce Type: replace-cross Abstract: Understanding gender biases in large language models (LLMs) is increasingly important as these systems become…
arXiv:2609.39374v1 Announce Type: cross Abstract: Synthetic time series are increasingly used for data augmentation, privacy-preserving data sharing, and downstream model…
arXiv:2609.39365v1 Announce Type: cross Abstract: Continual alignment requires LLMs to adapt to new requirements without forgetting previously acquired behaviors. Natural-language…
arXiv:2609.37002v2 Announce Type: replace-cross Abstract: High-resolution visual question answering often fails because a multimodal model does not acquire the small,…