Open Mind最新文献_第6页

Not All Authors Are Equal: Moral Judgments of Plagiarism From AI and Human Sources. 并非所有作者都是平等的：人工智能和人力资源剽窃的道德判断。

Open Mind Pub Date : 2026-02-15 eCollection Date: 2026-01-01 DOI: 10.1162/OPMI.a.336

Calahndra Brake, Kang Lee, Ori Friedman

{"title":"Not All Authors Are Equal: Moral Judgments of Plagiarism From AI and Human Sources.","authors":"Calahndra Brake, Kang Lee, Ori Friedman","doi":"10.1162/OPMI.a.336","DOIUrl":"10.1162/OPMI.a.336","url":null,"abstract":"Generative AI tools are increasingly being used for creative and academic work. How do people morally evaluate plagiarism involving AI-generated content, and do they judge it differently than when the source is a human? Investigating these questions can provide insight into why people condemn plagiarism; for instance, whether this is due to harm to the original creator or the false benefit gained by the plagiarizer. We examined people's moral evaluations of plagiarism involving AI-generated content in five experiments (N = 1705). In each experiment, participants read scenarios about a poet submitting someone else's poem to a contest without credit. We compared three source types: a friend, ChatGPT, and a little-known poetry blog. In Experiments 1-3, participants judged plagiarism from the blog as more immoral than plagiarism from a friend or ChatGPT, with little difference between the latter two. Moral condemnation increased with the amount of content copied and remained stable when compared to other moral transgressions. In Experiments 4 and 5, moral judgments became harsher when human sources (friend or blog) denied permission, but not when ChatGPT did, suggesting that its refusal was not treated as morally meaningful. When all sources granted permission, differences between conditions disappeared. Overall, these findings support both the harm and false benefit accounts of why people condemn plagiarism. The findings also advance knowledge about how, and when, permission from the source affects condemnation of plagiarism.","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"10 ","pages":"216-235"},"PeriodicalIF":0.0,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13053024/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147634413","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Search Efficiency Drives Reference Production Across Modalities, But Colour Is Special. 搜索效率驱动各种形式的参考生产，但颜色是特殊的。

Open Mind Pub Date : 2026-02-15 eCollection Date: 2026-01-01 DOI: 10.1162/OPMI.a.337

Merrick Giles, Paula Rubio-Fernandez, Francis Mollica

{"title":"Search Efficiency Drives Reference Production Across Modalities, But Colour Is Special.","authors":"Merrick Giles, Paula Rubio-Fernandez, Francis Mollica","doi":"10.1162/OPMI.a.337","DOIUrl":"10.1162/OPMI.a.337","url":null,"abstract":"When speakers refer to objects in the world, they frequently overinform. Contrary to classical theories in linguistics, we hypothesise that overinformativeness is an efficient means of facilitating listener comprehension: speakers use redundancy to provide their listeners with search-efficient perceptual information. In Experiment One (N = 72), we operationalise search efficiency as the ease or difficulty of perceptual discrimination. We borrow methods from psychophysics to manipulate discriminability across attributes (material, colour) and across sensory modalities (audition, vision). We show that across both attributes and modalities, speakers overinform more often when the redundant information helps the listener perceptually discriminate the referent, thus aiding listener-search. Contrary to our expectations, we also find that speakers disproportionately overinform with colour information (relative to material). In Experiment Two (N = 97), we investigate the disproportionate use of colour directly, addressing explanations that appeal to colour's perceptual salience by 1) dampening colour's perceptual distinctiveness, and 2) controlling linguistic complexity both in terms of language production and retrieval effort. Contrary to widespread explanations, these factors cannot explain the disproportionate use of colour: colour is privileged in reference.","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"10 ","pages":"236-260"},"PeriodicalIF":0.0,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13053021/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147634485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Chunking, Attraction, Repulsion, and Ensemble Effects Are Ubiquitous in Visual Working Memory. 组块、吸引、排斥和集合效应在视觉工作记忆中是普遍存在的。

Open Mind Pub Date : 2026-02-15 eCollection Date: 2026-01-01 DOI: 10.1162/OPMI.a.312

Chaipat Chunharas, Timothy F Brady

{"title":"Chunking, Attraction, Repulsion, and Ensemble Effects Are Ubiquitous in Visual Working Memory.","authors":"Chaipat Chunharas, Timothy F Brady","doi":"10.1162/OPMI.a.312","DOIUrl":"10.1162/OPMI.a.312","url":null,"abstract":"What happens when there are many different objects that must be maintained simultaneously in visual working memory? Prominent models focus largely on individual objects in describing memory limits: e.g., claims that we can remember only a fixed number of items, or that a single resource limit describes the cost of holding additional items. While some acknowledge interactions between items, these interactions are not given a prominent role in most models. Here we show that instead of items being represented independently, the visual display is always compressed by utilizing clusters of items and the gist of the display. We reanalyze data from 11 previously available datasets (comprising 137,986 trials in total). We find strong evidence for non-independent representations, including chunking and use of the 'gist' of the display, which is present in nearly every study at every set size. We then present a model for understanding this chunking and the resulting systematic biases (e.g., items attracting and repelling one another) based on psychophysical similarity. Overall, this work provides strong evidence that in order to understand visual working memory, we need to consider how our memory system takes advantage of the relationship between items. This is in contrast to the way the majority of the field studies visual working memory and suggests a major paradigm shift is required to think of memory in terms of clusters, chunks, and gist rather than in terms of independent items.","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"10 ","pages":"182-215"},"PeriodicalIF":0.0,"publicationDate":"2026-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13053025/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147634281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Children Understand How Adults' Achievement Goals Drive Actions. 孩子们理解成人的成就目标是如何驱动行动的。

Open Mind Pub Date : 2026-02-10 eCollection Date: 2026-01-01 DOI: 10.1162/OPMI.a.331

Brandon A Carrillo, Mika Asaba, Julia A Leonard

引用次数: 0

FMBench: Adaptive Large Language Model Output Formatting FMBench：自适应大语言模型输出格式

Open Mind Pub Date : 2026-02-06 DOI: 10.48550/arxiv.2602.06384

Yaoting Wang, Yun Zhou, Henghui Ding

{"title":"FMBench: Adaptive Large Language Model Output Formatting","authors":"Yaoting Wang, Yun Zhou, Henghui Ding","doi":"10.48550/arxiv.2602.06384","DOIUrl":"https://doi.org/10.48550/arxiv.2602.06384","url":null,"abstract":"Producing outputs that satisfy both semantic intent and format constraints is essential for deploying large language models in user-facing and system-integrated workflows. In this work, we focus on Markdown formatting, which is ubiquitous in assistants, documentation, and tool-augmented pipelines but still prone to subtle, hard-to-detect errors (e.g., broken lists, malformed tables, inconsistent headings, and invalid code blocks) that can significantly degrade downstream usability. We present FMBench, a benchmark for adaptive Markdown output formatting that evaluates models under a wide range of instruction-following scenarios with diverse structural requirements. FMBench emphasizes real-world formatting behaviors such as multi-level organization, mixed content (natural language interleaved with lists/tables/code), and strict adherence to user-specified layout constraints. To improve Markdown compliance without relying on hard decoding constraints, we propose a lightweight alignment pipeline that combines supervised fine-tuning (SFT) with reinforcement learning fine-tuning. Starting from a base model, we first perform SFT on instruction-response pairs, and then optimize a composite objective that balances semantic fidelity with structural correctness. Experiments on two model families (OpenPangu and Qwen) show that SFT consistently improves semantic alignment, while reinforcement learning provides additional gains in robustness to challenging Markdown instructions when initialized from a strong SFT policy. Our results also reveal an inherent trade-off between semantic and structural objectives, highlighting the importance of carefully designed rewards for reliable formatted generation. Code is available at: https://github.com/FudanCVL/FMBench.","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2026-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147878371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Iconicity Gives Communicators a Head-Start, Even if Only the Producer Experiences It. 象似性给了传播者一个先机，即使只有制作人体验到它。

Open Mind Pub Date : 2026-02-01 eCollection Date: 2026-01-01 DOI: 10.1162/OPMI.a.327

Robert Snider, Petros Kaklamanis, Gareth Roberts

{"title":"Iconicity Gives Communicators a Head-Start, Even if Only the Producer Experiences It.","authors":"Robert Snider, Petros Kaklamanis, Gareth Roberts","doi":"10.1162/OPMI.a.327","DOIUrl":"10.1162/OPMI.a.327","url":null,"abstract":"Iconicity has increasingly come to be recognized as widespread in language. It plays a particularly important role in bootstrapping new referring expressions in existing languages and in the emergence of new languages and other communication systems. The basis of this role has long been assumed to depend primarily on transparency of the iconic signal for the receiver, who benefits from being better able to identify its meaning. But might there also be producer-side advantages, distinct from this transparency-based comprehension benefit, that support communication? We investigated this using an experimental referential communication game in which dyads used a novel signaling medium to communicate fruits and vegetables. We manipulated both whether the producer could generate iconic signals and whether the receiver saw iconic or arbitrary signals. Results suggested that there was an iconicity benefit via stability in production even if the receiver was unable to perceive the iconicity (and therefore unable to benefit from transparency). However, while this gave dyads a substantial head-start, the lack of a benefit from iconicity for the receiver meant dyads in this condition still performed significantly less well overall than dyads with full iconicity.","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"10 ","pages":"118-159"},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13053026/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147634310","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A Resource-Rational Account of Human Eye Movements During Immersive Visual Search. 沉浸式视觉搜索过程中人眼运动的资源理性解释。

Open Mind Pub Date : 2026-02-01 eCollection Date: 2026-01-01 DOI: 10.1162/OPMI.a.322

Angela Radulescu, Bas van Opheusden, Frederick Callaway, Thomas L Griffiths, James M Hillis

{"title":"A Resource-Rational Account of Human Eye Movements During Immersive Visual Search.","authors":"Angela Radulescu, Bas van Opheusden, Frederick Callaway, Thomas L Griffiths, James M Hillis","doi":"10.1162/OPMI.a.322","DOIUrl":"10.1162/OPMI.a.322","url":null,"abstract":"The nature of eye movements during visual search has been widely studied in cognitive science. Virtual reality (VR) paradigms are an opportunity to test whether computational models of search can predict naturalistic search behavior. However, existing ideal observer models are constrained by strong assumptions about the structure of the world, rendering them impractical for modeling the complexity of environments which can be studied in VR. To address these limitations, we modeled immersive visual search as a reinforcement learning problem, in which sequential decisions are made over a multidimensional representation of the environment learned by a convolutional neural network. In our formulation, RL agents learned a policy over latent states-effectively solving what is known as a meta-Markov decision process (meta-MDP), where each decision concerns how to allocate attention to information in the environment. Training deep-RL agents on the meta-MDP showed that learned (i.e., optimal) search policies converge to a classic ideal-observer model of search developed for simple (1D) stimuli. We compared the learned resource-rational policy with human gaze data from a visual-search experiment conducted in VR and found qualitative and quantitative alignment between model predictions and human behavior. However, both the model's simulated performance and its correspondence with human behavior depended strongly on the representational features available to the policy. These results suggest that naturalistic visual search behavior can partially be explained by resource-rational allocation of limited cognitive resources, and the choice of representation influences the degree of alignment between model and human behavior.","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"10 ","pages":"91-117"},"PeriodicalIF":0.0,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13053022/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147634274","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Detection, Inspection, Return: An Object-Based Classification and Metric of Fixations in Complex Scenes. 检测、检查、返回：复杂场景中基于对象的注视分类和度量。

Open Mind Pub Date : 2026-01-15 eCollection Date: 2026-01-01 DOI: 10.1162/OPMI.a.319

Marcel Linka, Benjamin de Haas

{"title":"Detection, Inspection, Return: An Object-Based Classification and Metric of Fixations in Complex Scenes.","authors":"Marcel Linka, Benjamin de Haas","doi":"10.1162/OPMI.a.319","DOIUrl":"10.1162/OPMI.a.319","url":null,"abstract":"Analyses of human gaze behaviour towards complex scenes typically aim to explain heatmaps or scan-paths. While heatmaps lack temporal information, scan-paths aim for a level of detail which often is impractical. We introduce a novel approach, based on the premise that most fixations target objects and do so in meaningfully different ways, depending on temporal context: Detection fixations (D) foveate an object for the first time; Inspection fixations (I) successively target object details; and Return fixations (R) revisit a previously fixated object after going elsewhere. To test the hypothesis that these classes capture distinct fixation profiles, we reanalysed a large dataset of scene fixations. We computed separate heatmaps for D, I, and R and found significantly higher inter-observer consistency within than between classes. Across fixations landing on different semantic features, the proportion of D, I, and R fixations varied consistently, and a semantic salience model trained to predict each type of fixations independently learned diverging distributions of feature weights. Further, we found a shift from D to I and R across viewing time, in line with previous findings on ambient and focal viewing modes. We tested and confirmed that the dynamics of this shift varied as a function of trial duration. Finally, we highlight the recent application of the D, I, R classification as a metric for gaze comparisons in the context of dynamic scenes, in which scan-path similarity metrics fail. We propose the D, I, and R classification as a computationally simple yet powerful tool to classify spatiotemporal aspects of scene fixations in an object-based and intuitive manner and provide well-documented code to implement it. Future research may explore potential functional differences between D, I, and R fixations.","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"10 ","pages":"47-65"},"PeriodicalIF":0.0,"publicationDate":"2026-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13053019/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147634314","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

How Prediction of the Future Affects Encoding of the Present: Cooperation or Competition? 对未来的预测如何影响对现在的编码：合作还是竞争？

Open Mind Pub Date : 2026-01-15 eCollection Date: 2026-01-01 DOI: 10.1162/OPMI.a.329

Brynn E Sherman

{"title":"How Prediction of the Future Affects Encoding of the Present: Cooperation or Competition?","authors":"Brynn E Sherman","doi":"10.1162/OPMI.a.329","DOIUrl":"10.1162/OPMI.a.329","url":null,"abstract":"Each day brings new experiences and the opportunity to form new episodic memories. However, our everyday experiences are not isolated episodes; rather, there is significant spatial and temporal structure that holds across experiences, allowing us to build up structured knowledge about the world. We can then leverage this known structure to make predictions about how new experiences will unfold. In a recent study in Open Mind, Poskanzer, Tarder-Stoll, et al. found that such predictions benefitted episodic memory. Specifically, on trials in which participants were successfully able to make predictions about an upcoming experience, participants were more likely to encode that predictive information into memory. These findings seem to stand in stark contrast to other recent work, which found the opposite of worse episodic memory for predictive cues (Sherman et al., 2022; Sherman & Turk-Browne, 2020). How can these discrepant findings be reconciled? Here, I discuss several key task differences that might explain the discrepancy and highlight avenues for future research which might help to theoretically disentangle the contexts under which prediction may impede vs. facilitate episodic encoding.","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"10 ","pages":"79-90"},"PeriodicalIF":0.0,"publicationDate":"2026-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13053018/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147634340","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Using Artificial Neural Networks to Relate External Sensory Features to Internal Decisional Evidence. 利用人工神经网络将外部感官特征与内部决策证据联系起来。

Open Mind Pub Date : 2026-01-15 eCollection Date: 2026-01-01 DOI: 10.1162/OPMI.a.317

Marshall L Green, Mingjia Hu, Rachel N Denison, Dobromir Rahnev

{"title":"Using Artificial Neural Networks to Relate External Sensory Features to Internal Decisional Evidence.","authors":"Marshall L Green, Mingjia Hu, Rachel N Denison, Dobromir Rahnev","doi":"10.1162/OPMI.a.317","DOIUrl":"10.1162/OPMI.a.317","url":null,"abstract":"All theories of perceptual decision-making postulate that external sensory information is transformed into the internal evidence that is used to judge the identity of the stimulus. However, the nature of this external-to-internal transformation is generally unknown. In two experiments, we examined how a particular stimulus feature-orientation-is transformed into internal evidence. Subjects judged whether Gabors were tilted clockwise or counterclockwise. The results of Experiment 1 demonstrated that increasing the stimulus tilt in fine-scale increments resulted in a linear increase in sensitivity. However, the results of Experiment 2 demonstrated that increasing the stimulus tilt in coarse-scale increments had little effect on sensitivity, suggesting a highly non-linear transformation. Critically, artificial neural networks (ANNs) trained on the orientation task reproduced the empirical results, providing a framework for examining this external-to-internal transformation. The ANNs' internal activations revealed that fine-scale increments in tilt magnitude results in increasingly greater discriminability between the stimulus categories, but the degree of discriminability does not increase further after tilt magnitude becomes sufficiently large. Taken together, these results begin to reveal how external sensory information is transformed into the internal evidence that is used to judge the identity of a stimulus and suggest that ANNs could serve as a platform for understanding the mechanism underlying this critical transformation.","PeriodicalId":32558,"journal":{"name":"Open Mind","volume":"10 ","pages":"29-46"},"PeriodicalIF":0.0,"publicationDate":"2026-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13053016/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147634456","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0