cs.HC papers | Gist.Science

Characterizing Healthy & Post-Stroke Neuromotor Behavior During 6D Upper-Limb Isometric Gaming: Implications for Design of End-Effector Rehabilitation Robot Interfaces

This study leverages the OpenRobotRehab 1.0 dataset to analyze how interface design and task constraints influence neuromotor behavior in healthy and post-stroke users during 6D isometric gaming, demonstrating that pathological features are detectable in end-effector force data and that a novel hidden Markov model based on sEMG signals effectively classifies neuromotor dynamics where traditional synergy-based methods fail, thereby informing the design of adaptive rehabilitation robots.

Ajay Anand, Gabriel Parra, Chad A. Berghoff, Laura A. HallockThu, 12 Ma💻 cs

Dance2Hesitate: A Multi-Modal Dataset of Dancer-Taught Hesitancy for Understandable Robot Motion

This paper introduces "Dance2Hesitate," an open-source multi-modal dataset comprising synchronized kinesthetic robot teaching and dancer motion capture data across three hesitancy levels, designed to facilitate the study and benchmarking of understandable, context-aware hesitancy in human-robot collaboration.

Srikrishna Bangalore Raghu, Anna Soukhovei, Divya Sai Sindhuja Vankineni, Alexandra Bacula, Alessandro RonconeThu, 12 Ma💻 cs

Reactive Writers: How Co-Writing with AI Changes How We Engage with Ideas

This mixed-methods study introduces the concept of "Reactive Writing," revealing that co-writing with AI shifts the process from traditional ideation to an evaluation-first approach where writers unconsciously adopt AI-suggested ideas and opinions while maintaining an illusion of full control.

Advait Bhat, Marianne Aubin Le Quéré, Mor Naaman, Maurice JakeschThu, 12 Ma🤖 cs.AI

Large Language Model Psychometrics: A Systematic Review of Evaluation, Validation, and Enhancement

This systematic review introduces the emerging interdisciplinary field of LLM Psychometrics, which applies psychometric theories and instruments to develop comprehensive evaluation frameworks for measuring human-like psychological constructs in large language models, ultimately guiding the creation of more robust, human-centered AI systems.

Haoran Ye, Jing Jin, Yuhang Xie, Xin Zhang, Guojie SongThu, 12 Ma💬 cs.CL

NasoVoce: A Nose-Mounted Low-Audibility Speech Interface for Always-Available Speech Interaction

NasoVoce is a nose-mounted speech interface that fuses acoustic and vibration signals to enable robust, discreet, and always-available voice interaction for AI, effectively overcoming the limitations of existing silent and whispered speech recognition methods.

Jun Rekimoto, Yu Nishimura, Bojian YangThu, 12 Ma🤖 cs.AI

Conversational AI-Enhanced Exploration System to Query Large-Scale Digitised Collections of Natural History Museums

This paper presents a human-centred system design that leverages conversational AI and function-calling capabilities to enable natural language querying and visual-spatial exploration of nearly 1.7 million digitised natural history specimen records at the Australian Museum, overcoming the limitations of traditional keyword-based search tools.

Yiyuan Wang, Andrew Johnston, Zoë Sadokierski, Rhiannon Stephens, Shane T. AhyongThu, 12 Ma🤖 cs.AI

DUCTILE: Agentic LLM Orchestration of Engineering Analysis in Product Development Practice

This paper introduces DUCTILE, an agentic LLM orchestration framework that separates adaptive decision-making from deterministic tool execution to automate engineering analysis in product development, successfully handling input deviations in an aerospace case study while highlighting the emerging tension between task automation and the creation of exhausting supervisory roles.

Alejandro Pradas-Gomez, Arindam Brahma, Ola IsakssonThu, 12 Ma🤖 cs.AI

Design and Quantitative Evaluation of an Embedded EEG Instrumentation Platform for Real-Time SSVEP Decoding

This paper presents and quantitatively evaluates an embedded EEG platform based on an ESP32-S3 and ADS1299 that achieves real-time, closed-loop SSVEP decoding with high measurement integrity, demonstrating 99.17% online accuracy and 27.66 bits/min information transfer rate entirely on-device.

Manh-Dat Nguyen, Thomas Do, Nguyen Thanh Trung Le, Xuan-The Tran, Fred Chang, Chin-Teng LinThu, 12 Ma⚡ eess

Toward Epistemic Stability: Engineering Consistent Procedures for Industrial LLM Hallucination Reduction

This paper presents and evaluates five prompt engineering strategies for reducing LLM hallucinations in industrial settings without modifying model weights, finding that an Enhanced Data Registry (M4) achieved perfect consistency in initial trials while a revised Decomposed Model-Agnostic Prompting (M2) showed the most significant improvement in subsequent verification.

Brian Freeman, Adam Kicklighter, Matt Erdman, Zach GordonThu, 12 Ma🤖 cs.AI

A Governance and Evaluation Framework for Deterministic, Rule-Based Clinical Decision Support in Empiric Antibiotic Prescribing

This paper proposes a governance and evaluation framework for deterministic, rule-based clinical decision support systems in empiric antibiotic prescribing that prioritizes transparency, auditability, and conservative behavior by formally separating decision logic from scope constraints and utilizing synthetic case validation to ensure behavioral alignment with predefined rules.

Francisco José Gárate, Paloma Chausa, Diego Moreno, Judit López Luque, Vicens Díaz-Brito, Enrique Javier GómezThu, 12 Ma🤖 cs.AI

Dark Patterns and Consumer Protection Law for App Makers

This paper examines how both intentional and unintentional dark patterns in app design undermine consumer autonomy, offering strategies for developers to navigate emerging consumer protection laws by adopting transparent choice architecture to ensure compliance and build user trust.

Gregory M. DickinsonThu, 12 Ma💻 cs

Technological folie à deux: Feedback Loops Between AI Chatbots and Mental Illness

This paper argues that the interaction between human cognitive biases and AI chatbot behaviors like sycophancy creates dangerous feedback loops that can destabilize beliefs and exacerbate mental illness, necessitating coordinated interventions across clinical, technical, and regulatory domains.

Sebastian Dohnány, Zeb Kurth-Nelson, Eleanor Spens, Lennart Luettgau, Alastair Reid, Iason Gabriel, Christopher Summerfield, Murray Shanahan, Matthew M NourThu, 12 Ma🧬 q-bio

G-STAR: End-to-End Global Speaker-Tracking Attributed Recognition

The paper proposes G-STAR, an end-to-end system that integrates a time-aware speaker-tracking module with a Speech-LLM backbone to achieve robust, timestamped speaker-attributed recognition for long-form, overlapping multi-party speech while maintaining global identity consistency.

Jing Peng, Ziyi Chen, Haoyu Li, Yucheng Wang, Duo Ma, Mengtian Li, Yunfan Du, Dezhu Xu, Kai Yu, Shuai WangThu, 12 Ma⚡ eess

Empathy Is Not What Changed: Clinical Assessment of Psychological Safety Across GPT Model Generations

This study refutes the claim that newer AI models have lost empathy, demonstrating through clinical assessment that while empathetic responses remain statistically consistent across generations, users' perception of "lost empathy" actually stems from a significant shift toward heightened crisis detection and altered safety postures that make the models appear more intrusive during vulnerable moments.

Michael Keeman, Anastasia KeemanThu, 12 Ma💬 cs.CL

Nurture-First Agent Development: Building Domain-Expert AI Agents Through Conversational Knowledge Crystallization

This paper proposes Nurture-First Development (NFD), a paradigm that shifts AI agent creation from static engineering to a continuous, conversational co-evolution process with domain experts, utilizing a Knowledge Crystallization Cycle to progressively transform tacit operational dialogue into structured, reusable expertise.

Linghao ZhangThu, 12 Ma🤖 cs.AI

CUAAudit: Meta-Evaluation of Vision-Language Models as Auditors of Autonomous Computer-Use Agents

This paper presents CUAAudit, a large-scale meta-evaluation demonstrating that while Vision-Language Models can serve as autonomous auditors for Computer-Use Agents with strong accuracy and calibration, their significant performance degradation in complex environments and notable inter-model disagreement reveal fundamental limitations that necessitate explicit accounting for evaluator reliability and uncertainty in real-world deployments.

Marta Sumyk, Oleksandr KosovanThu, 12 Ma🤖 cs.AI

From OCR to Analysis: Tracking Correction Provenance in Digital Humanities Pipelines

This paper proposes a provenance-aware framework for tracking OCR correction lineage in digital humanities pipelines, demonstrating that recording edit details at the span level significantly improves the reproducibility and interpretability of downstream NLP tasks by revealing how textual transformations impact scholarly analysis.

Haoze Guo, Ziqi WeiMon, 09 Ma💻 cs

Safe Autonomous Lane Changing: Planning with Dynamic Risk Fields and Time-Varying Convex Space Generation

This paper proposes a novel autonomous lane-changing planning framework that integrates dynamic risk fields with time-varying convex feasible spaces and a constrained iLQR solver to achieve safe, efficient, and comfortable trajectories that outperform traditional methods in complex traffic scenarios.

Yijun Lu, Zhihao Lin, Zhen TianMon, 09 Ma💻 cs

Indicating Robot Vision Capabilities with Augmented Reality

This paper proposes and evaluates four augmented reality indicators designed to visualize a robot's field of view, finding that allocentric indicators placed in the task space and egocentric indicators modifying the robot's eyes effectively improve human accuracy in collaborative tasks while maintaining high confidence and low cognitive load.

Hong Wang, Ridhima Phatak, James Ocampo, Zhao HanMon, 09 Ma💻 cs

Pre/Absence: Prompting Cultural Awareness and Understanding for Lost Architectural Heritage in Virtual Reality

This paper presents "Pre/Absence," a virtual reality experience that leverages the dialectic of presence and absence to transform the interpretation of lost architectural heritage from static factual summaries into a nuanced, emotionally engaging narrative that fosters deeper cultural awareness and critical reflection on the evolving meanings of heritage.

Yaning Li, Ke Zhao, Shucheng Zheng, Xingyu Chen, Chenyi Chen, Wenxi Dai, Weile Jiang, Qi Dong, Yiqing Zhao, Meng Li, Lin-Ping YuanMon, 09 Ma💻 cs

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