Social-physical human-robot interaction (spHRI) has grown rapidly across robotics, human-computer interaction, human-robot interaction, and haptics. Yet, fragmented terminology and inconsistent methodologies make systematic synthesis difficult.
arXiv:2606. 26382v1 Announce Type: cross Abstract: Social-physical human-robot interaction (spHRI) has grown rapidly across robotics, human-computer interaction, human-robot interaction, and haptics.
The paper introduces CoSLR, a Human‑AI collaborative system for systematic literature reviews that incorporates mandatory human checkpoints within a three‑phase pipeline using large language models and Retrieval‑Augmented Generation. In a survey of 63 participants, 42.9 % rated the system’s usability highly, yet 34.9 % indicated they would trust AI‑generated summaries without further human verification after brief interaction. The study highlights that effective human oversight in AI‑assisted literature reviews depends on users’ willingness to engage with the checkpoints, underscoring a calibration issue that interface design must directly address.
arXiv:2605. 03202v2 Announce Type: replace Abstract: Large language models offer a tempting solution to address the peer review crisis.
AI-assisted peer review is increasingly discussed and adopted as a tool to support the scientific publishing process, yet there is little systematic understanding of how publication venues regulate its use or of how capable current AI review systems are. We address these questions by first surveying reviewer-facing AI policies across 111 leading AI/NLP conferences and medical journals, revealing substantial regulation differences between the two communities.
arXiv:2608.21374v1 Announce Type: new Abstract: Literature reviews are essential to scientific progress, but rigorously evaluating automatically generated reviews remains difficult because many aspec...
arXiv:2511. 13480v2 Announce Type: replace-cross Abstract: This study focuses on understanding the complex dynamics between humans and AI systems by analyzing user reviews.
The paper "Why did My Robot Just Change Personality? Prompting Guidelines for a Grounded Robot Persona in LLM-Based HRI" addresses the lack of clear prompt design in human‑robot interaction using large language models. It proposes a framework and a structured prompt template with eight functional components to specify, bound, and adapt robot behavior. The authors base their guidelines on a review of prior work and on survey data from 27 HRI experts, highlighting issues such as unclear robot personality, the need for user adaptation, and ethical concerns around safety, deception, and governance.
Context: Generative AI (GenAI) and Large Language Models (LLMs) are increasingly used for academic tasks in software engineering and beyond, including systematic literature reviews (SLRs). However, while capable of summarizing text, there is no guarantee they can meet the rigour, reliability, and transparency that SLRs require.
arXiv:2608. 03581v1 Announce Type: cross Abstract: AI-assisted peer review is increasingly discussed and adopted as a tool to support the scientific publishing process, yet there is little systematic understanding of how publication venues regulate its use or of how capable current AI review systems are.
arXiv:2506. 08134v4 Announce Type: replace Abstract: Peer review, the bedrock of scientific advancement in machine learning (ML), is strained by a crisis of scale.
The paper introduces Vocalizer, a mobile app that lets users submit spoken online reviews enhanced by a large language model. A longitudinal study shows that users often use the AI to add detail and that interactive AI features boost confidence and willingness to share reviews. The authors also outline the benefits and challenges of embedding AI assistance in review-writing systems.
arXiv:2604. 01463v2 Announce Type: replace-cross Abstract: Physically Assistive Robots require personalized behaviors to ensure user safety and comfort.