…improving agent safety comes at the cost of degraded task performance . Such sparse and single-objective rewards severely limit real-world usability. To bridge this gap, we propose FATE, an on-policy…
…a Long-Horizon Memory Environment for LLM Agents (2026) MementoGUI: Learning Agentic Multimodal Memory Control for Long-Horizon GUI Agents (2026) When Stored Evidence Stops Being Usable: Scale-Conditioned Evaluation of Agent…
…Work focuses on improving the efficiency and robustness of distributed black box optimization in multi-agent systems. Potential applications include cooperative sensing, resource allocation, and distributed control, which may contribute to more…
…Only a file-based agent paired with Claude Opus 4.7 as its internal LLM partially closes the gap, but at ~70x the baseline cost, indicating closure currently depends on configurations that…
…cost, two strong general AI-scientist baselines ( ARIS , DeepScientist ) execute partial CFD workflows but lack the domain-specific validity gates needed to convert runs into defensible scientific claims; and a controlled planted…
…UAVs hit connectivity gaps, closed-loop control can't tolerate round-trips, and per-token pricing caps sustained agentic deployments. On-device LLMs hit the opposite wall: compute, memory, capability. This survey…
…The following papers were recommended by the Semantic Scholar API Push Your Agent: Measuring and Enforcing Quantitative Goal Persistence in Long-Horizon LLM Agents (2026) RubricRefine: Improving Tool-Use Agent Reliability with…
Papers arxiv:2605.11711 Debiased Model-based Representations for Sample-efficient Continuous Control Published on May 12 Submitted by Jiafei Lyu on May 13 Tencent Hunyuan Authors: , , , Kai Yang , , , , Abstract DR.Q…
…control branches, or attention and positional-encoding modifications, which often require post-training on large-scale camera-annotated videos. Training-free alternatives avoid such post-training, but often shift the cost to…
…AI-generated summary While Test-Time Scaling (TTS) offers a promising direction to enhance video generation without the surging costs of training, current test-time video generation methods based on diffusion models…