Tool use, function calling, orchestration and the protocols that let models act rather than only answer.
arXiv:2610.17126v1 Announce Type: cross Abstract: The rapid proliferation of autonomous AI agents in decentralized ecosystems challenges existing identity paradigms. While human identity is tradition...
arXiv:2610.17418v1 Announce Type: cross Abstract: Agentic workflows combine large language models with planning, memory, tools, execution environments, and iterative feedback. Their failures are diff...
arXiv:2610.17444v1 Announce Type: cross Abstract: Language model (LM) agents can fail for different reasons, requiring different explanations and interventions. We study how state beliefs, action val...
arXiv:2610.17694v1 Announce Type: cross Abstract: We introduce HelpMeOut, an embodied AI benchmark for error-aware monitoring of household task execution. Existing embodied household benchmarks typic...
arXiv:2610.17685v1 Announce Type: cross Abstract: Enterprise agents face safety risks that cannot be determined from individual actions alone. Existing safety benchmarks largely evaluate action-local...
arXiv:2610.17747v1 Announce Type: cross Abstract: Failure-attribution benchmarks ask an LLM judge which step or agent caused a failure. A high score should mean the judge checked the faulty step agai...
arXiv:2610.18097v1 Announce Type: cross Abstract: Post-training is crucial for improving text-to-image models, yet existing pipelines typically rely on manually curated training data and fixed traini...
arXiv:2610.18305v1 Announce Type: cross Abstract: The world encompasses both physical environments and human actors. Predicting its evolution requires understanding both physical laws and how emotion...
arXiv:2610.18356v1 Announce Type: cross Abstract: City-scale 3D grounding is commonly formulated as candidate ranking, which requires precomputed instance proposals and becomes inefficient in large o...
arXiv:2610.18420v1 Announce Type: cross Abstract: We trained Agaram 2.5B, a 2.5-billion-parameter Tamil-English language model, from scratch on about 50 billion tokens (58% Tamil, the rest English, m...
arXiv:2610.18417v1 Announce Type: cross Abstract: End-to-end deep learning pipelines for camera-radar 3D object detection are well established in driver assistance systems and autonomous vehicles; ho...
arXiv:2610.18686v1 Announce Type: cross Abstract: 3D semantic occupancy prediction is crucial for autonomous driving, but camera-based methods degrade in low-light conditions and LiDAR-based methods...
arXiv:2610.18861v1 Announce Type: cross Abstract: How can we build an agent that thinks beyond human language, yet still acts through it in the external environment? Modern LLM agents still reason an...
arXiv:2610.18862v1 Announce Type: cross Abstract: Reasoning models achieve strong performance through long chains of thought (CoT), but often spend more tokens than needed to solve a problem. Existin...
arXiv:2610.18868v1 Announce Type: cross Abstract: Long-horizon agents have drawn growing attention for their ability to work autonomously -- from hours to days -- on economically valuable tasks, a ca...
arXiv:2610.18874v1 Announce Type: cross Abstract: Agentic robotics places a large language model (LLM) agent in the robot control loop, where it composes perception, motion, and vision-language-actio...
arXiv:2509.03736v3 Announce Type: replace Abstract: LLM agents are increasingly proposed as substitutes for human participants in social research, usually on the strength of survey responses that mat...
arXiv:2510.22833v3 Announce Type: replace Abstract: While reinforcement learning agents can achieve superhuman performance in many complex tasks, they typically do not become more computationally eff...
arXiv:2601.11100v3 Announce Type: replace Abstract: Large Language Model (LLM) agents are reshaping the industrial landscape. However, most practical agents still rely on human-designed scaffolds, ma...
arXiv:2602.03100v2 Announce Type: replace Abstract: Large Language Models (LLMs) are increasingly deployed as agents that operate in real-world environments, introducing safety risks beyond linguisti...