Applied & Human-Centered · Computer Science & AI
Human-Computer Interaction
The newest papers in Human-Computer Interaction that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
1,000 papers, from 31 August 2026 to 5 November 2026: 993 arXiv preprints and 7 OpenAlex records.
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Newest papers, page 41
Neither Silence nor Overlap Is Failure: Intent-Conditioned Evaluation of Turn-Taking in Full-Duplex Spoken Dialogue Models
Benchmarks for full-duplex spoken dialogue models score turn-taking with binary fixed-window rules that reward immediate response or silence by completeness of the prior turn.Psychoacoustically Aligned Latent Smoothing for Adversarial Robustness of Full-Duplex Speech-to-Speech Dialogue Models
End-to-end speech-to-speech dialogue models listen and speak simultaneously, so a continuously open acoustic channel is exposed to adversarial manipulation.When Visual Quality Misleads: Intent Recognition under Rendered Avatar Distortions
Avatar-streaming systems are commonly evaluated with image and video quality assessment (IQA/VQA) metrics, implicitly treating visual fidelity as a proxy for communicative success.Brain-to-Language Decoding: Tasks, Signals, Methods, Evaluation, Practical Use and Beyond
Brain-to-language decoding translates neural activity associated with language production, internal speech and perception into linguistic or expressive outputs.LLM-Assisted Workflow for Structural Difference Visualization in Evolving Software Requirements
This paper presents an LLM-assisted workflow for visualizing structural differences in evolving software require- ments.Talk2Escape: Conversational Grounding for Vision-and-Language Navigation
While Vision-and-Language Navigation (VLN) has demonstrated remarkable success, the prevailing single-turn paradigm exposes a fundamental vulnerability: agents operate in a strictly open-loop manner.When the Strike Zone Becomes Algorithmic: Umpire Judgment and Player Challenge Decisions under AI Review
The Automated Ball-Strike challenge system that Major League Baseball adopted in 2026 offers a distinctive setting for studying human AI interaction in which umpires make every ball and strike call…Deflecting the Value Compass: Interacting with Large Language Models Temporarily Shifts Human Value Priorities Toward Personal Focus
Large language models increasingly support decisions where values are in tension, yet little is known about whether interacting with them changes which values users prioritize.Faithful Faithfulness Evaluations: Challenges & Pitfalls Learned from a Breast MRI Case Study
Saliency maps are widely used to explain deep learning predictions in medical imaging, yet visually plausible explanations do not necessarily reflect a model's true decision process and may…Benchmarking Robots for Everyday Environments: From Lab Experiments to Real-World Operations
This study introduces an interdisciplinary framework for benchmarking robots deployed in public environments, addressing the gap between traditional laboratory metrics and real-world benchmarking…Do Vision Model See Like the Brain? A Comparison Across EEG Encoding Model
Convolutional neural networks (CNNs) and vision transformers are both used to model the human visual system, but whether the two architectures diverge at a specific point in network depth is unclear.Receptiveness, Not Sycophancy: Distinguishing Engagement from Deference in Language Models
A central concern with language models is sycophancy: their tendency to defer to users' views at the expense of independent substantive judgment.Does AI Save Time on Product Design? A Randomized Controlled Experiment of AI Prompt-to-Design Workflows
AI tools for digital product design now offer prompt-to-design capabilities, allowing designers and their non-designer colleagues to create prototypes through conversational workflows with large…Safety Nudges: User-Facing Interventions for Real-Time AI Risk Awareness
Conversational AI systems can pose safety risks to their users such as hallucination, sycophancy, overconfidence, and anthropomorphism, but these risks are difficult for users to detect during…Experts Rise Where LLMs Disagree: Using Cross-Model Disagreement to Target Expert Effort in LLM Codebook Revision for Large-Scale Annotation
Large-scale text annotation brings expert insight to millions of documents, often through a codebook that AI annotators follow.Building Socio-Affective Artificial Intelligence for Interactive Multi-Agent Simulations
The objective of this article is to provide design principles and a software architecture for enabling interaction between humans and multiple agents in simulated dynamic worlds.ContraVis: Evidence-Grounded Visual Analytics for Contradiction Review in Legal Contracts
Legal contracts are structurally complex documents in which contradictions may emerge across distant and interconnected provisions.Toward Human-in-the-Loop Robot Failure Recovery: Bridging Communication Gaps in Human-Robot Collaboration
Robots can recover from failures by asking bystanders for help, but effective human-in-the-loop recovery requires communication that accounts for differences in people's knowledge.WidgetVA: A Widget-Centric Framework and Benchmark for Agentic Visual Analytics
Visual analytics (VA) enables sensemaking through interactive visualization, but effective analysis often requires experts to translate high-level intents into long sequences of interface operations…Ask Before It Tells: Benchmark-to-Robot Body-Cue Transfer for a Question-First Bedside Robot
Body-cue recognition can support assistive robots, but benchmark accuracy does not guarantee reliable behavior under a robot-camera viewpoint.