AI agents

Tool use, function calling, orchestration and the protocols that let models act rather than only answer.

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arXiv AI
Aug 18

Handoff-H1: An Orchestrated Vision-Agent System for Material Quantity Takeoff from Construction Blueprints

arXiv:2608. 15032v1 Announce Type: cross Abstract: Converting a set of architectural blueprints into a complete material quantity takeoff requires visual perception across drawing sheets, dimensional and multi-hop reasoning, and grounding in construction conventions that the drawings never state.

By Bruno Chicelli, Henrique Alves, Rodrigo Anselmo, Joshua Weinberg, Felipe Lemos, Jan Baryla
arXiv AI
Aug 18

GraniKV: Asymmetric Granularity KV-Cache Paging for Multi-Agent Systems with Long Shared Prefix

arXiv:2608. 15584v1 Announce Type: cross Abstract: Production paged-serving engines apply uniform paging granularity to the KV cache, even though the two regions of a multi-agent workload have opposite storage requirements: a long shared prefix demands contiguity, while the per-request suffix demands fine-grained allocation.

By Jinhyun Jeon, Sungjoo Yoo
arXiv AI
Aug 18

QUMem: Personalized Memory for Query-Conditioned User-State Inference in LLM Agents

arXiv:2608. 16168v1 Announce Type: cross Abstract: Large language model (LLM) agents increasingly use external memory systems to support personalization by drawing on long and evolving interaction histories, in which user preferences may be distributed across time, change with context, and conflict with earlier evidence.

By Heng Wang, Yifei Li, Lingling Zhang, Pengyu Li, Xinyu Che, Xinyu Zhang, Zesheng Yang
arXiv AI
Aug 18

Neurosymbolic Embodied Agents

arXiv:2608. 16794v1 Announce Type: cross Abstract: Language and vision-language models generate plausible embodied plans but do not guarantee executability, as their outputs can violate environment dynamics or act on incorrectly grounded entities.

By Mohammad Albinhassan, Yuming Feng, Alessandra Russo, Pranava Madhyastha
arXiv Machine Learning
Aug 18

WANDR: A Benchmark for Wide and Deep Research

arXiv:2608. 14747v1 Announce Type: new Abstract: WANDR (Wide ANd Deep Research) is a benchmark of 500 realistic, challenging data-collection tasks for research agents.

By Vitaliy Polshkov, Marcin Pitera, Jeremy Yang, Kirill Priemko, Maksim Gaiduk, Aleksandr Nikolenko, Denis Bykov, Clare Southern, Denis Yarats, Jerry Ma
arXiv Machine Learning
Aug 18

The Ethical Decision Head: Operationalizing Normative Ethics in Autonomous Vehicles via Reinforcement Learning from Human Feedback

arXiv:2608. 16710v1 Announce Type: new Abstract: As autonomous vehicles (AVs) approach Level 4 and Level 5 operational capability [SAE International, 2018], their on- board decision systems must handle not only safety-critical locomotion but also their subsequent moral weight.

By Thomas Mbrice, Ammar Ali, Sami Mian, Khai Hern Low, Eric Chen, Arshia Aghajani, Wolf Sch\"afer, Amin Shirangi
arXiv AI
Aug 18

Emergent Misaligned Communication in Long-Horizon Multi-Agent LLM Commerce

arXiv:2608. 14825v1 Announce Type: cross Abstract: Frontier LLM agents increasingly transact on behalf of separate principals, often using natural language rather than structured APIs.

By Zeyuan Li (Massachusetts Institute of Technology), Lukas Petersson (Andon Labs), Alessandro Acquisti (Massachusetts Institute of Technology), Michiel A. Bakker (Massachusetts Institute of Technology)