United States

Humans rely on multimodal information to make judgements about events occurring in their environment. Haptic feedback, in particular, is essential to how people learn about and manipulate the objects they use daily. While much work has investigated how visual and auditory information affect the perception of causal events, little has explored how causal judgments change with the addition of haptic feedback. To begin addressing this question, we ran a psychophysical study based on the Michottean launching paradigm. We compared the use of visual and haptic with solely visual information during causally ambiguous collisions. We manipulated the offset between when the first object stops moving and the second object starts moving. Using a custom one degree-of-freedom haptic device, users in the vision and haptic condition received kinesthetic haptic feedback synchronized to the second object’s motion. The results demonstrate that adding haptic information increases causal perception for events with larger temporal offsets.

CogSci 2021

In Touch with Causation: Understanding the Impact of Kinesthetic Haptics on Causality

## Welcome!
"I am excited to welcome you to this year’s edition of the Conference on Empirical Methods in Natural Language Processing! Importantly, it marks the 30th edition of EMNLP. With over 8,000 submissions, more than 3,000 accepted papers, and thousands of attendees, we have come a long way from that first
workshop, which had 14 accepted papers. As the field looks ahead, Suzhou is the fitting location for celebrating this milestone: rooted in a long literary tradition, yet modern and forward-looking, and home to a large share of the NLP community."<br>

*Message from the General Chair, Dirk Hovy*





<br>

EMNLP 2025

Celebrate 30 Years of EMNLP! 
EMNLP 2025 will be held in Suzhou, China from November 5th to November 9th, 2025.

poster

### Looking for Cogsci 2023? Please [click here](https://underline.io/events/405/reception) to switch to 2023 edition.


**Dear Colleagues,**

Welcome to the 43rd Annual Conference of the Cognitive Science Society! 

This year’s conference brings together the latest research from all Cognitive Science and also highlights this year’s theme **Comparative Cognition: Animal Minds.** 

The program features four plenary speakers: Friederike Range (University of Veterinary Medicine, Vienna), Onur Güntürkün (Ruhr University Bochum), Julia Fischer (University of Göttingen), and Erich Jarvis (The Rockefeller University). The keynotes and invited symposia showcase the broad spectrum of ideas that encompass the conference theme of comparative cognition. 

Further, the program includes the Rumelhart Prize keynote presentation by Susan Goldin-Meadow (University of Chicago), and symposia to celebrate the winner of the Elman Prize: Wei Ji Ma (New York University), the Heineken Award winner Robert Zatorre (McGill University), and the Robert J. Glushko Dissertation Prizes session.

The program committee for CogSci 2021 received 1,025 submissions, including 710 full papers, 275 member abstracts, 8 publication-based talks, as well as 15 proposals for symposia, and 17 for workshops and tutorials. After a rigorous review process, the committee selected 152 papers for oral presentation and inclusion in the conference proceedings (14.8%), 332 papers for poster presentation and inclusion in the proceedings (32.4%), and 175 papers for poster presentation with inclusion of abstracts in the proceedings (17.1%) We also selected 275 submitted member abstracts. In addition, we accepted 6 publication-based talks, 12 symposia, and 9 workshops and tutorials to make for an exciting and inclusive program.

We hope that you enjoy the conference this year!<br><br>

**Your Program Chairs,**
![](https://assets.underline.io/uploads/markdown_image/1/image/99984908caba5e6453e5fc5ba34f3507.jpg)

**Learn more about the Vienna Cognitive Science Hub at the University of Vienna, hosts of CogSci 2021**

<iframe width="560" height="315" src="https://www.youtube.com/embed/464h1m3iU68" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>

To review the proceedings for the conference or review the searchable program, please visit the [website](https://cognitivesciencesociety.org/program/).


The Cognitive Science Society brings together researchers from around the world who hold a common goal: understanding the nature of the human mind. The mission of the Society is to promote Cognitive Science as a discipline, and to foster scientific interchange among researchers in various areas of study, including Artificial Intelligence, Linguistics, Anthropology, Psychology, Neuroscience, Philosophy, and Education. The Society is a non-profit professional organization and its activities include sponsoring an annual conference and publishing the journals Cognitive Science and TopiCS.

This study examined the nature of phonological processing in Chinese-character word recognition. Chinese and Japanese use similar linguistic notations. Previous studies have suggested that Japanese readers use abstract, non-articulatory phonology when they read two-character Japanese kanji words. We examined whether Chinese readers use the same process. In Experiment 1, 25 native Chinese speakers performed a homophone judgment task using two-character Chinese words. The participants made more errors in the articulatory suppression condition than in the control condition. This suggests that the phonological information used during the task was speech-like, articulatory phonology. In Experiment 2, 24 native Chinese speakers performed a homophone judgment task using one-character Chinese words. Articulatory suppression did not disrupt the performance. Chinese speakers should use non-articulatory phonology when they read one-character Chinese words. The results of two experiments indicate that phonological processing used by Chinese and Japanese readers are not the same.

Effects of articulatory suppression on the homophone judgments of Chinese-character words

Learning new languages is a complex cognitive task involving both implicit and explicit processes. Batterink, Oudiette, Reber, and Paller (2014) report that participants with vs. without conscious awareness of a hidden semi-artificial language regularity showed no significant differences in grammar learning, suggesting that implicit/explicit routes may be functionally equivalent. However, their operationalizing of learning via median reaction times might not capture underlying differences in cognitive processes. In a conceptual replication, we compared rule-aware (n=14) and rule-unaware (n=21) participants via drift-diffusion modeling, which can quantify distinct subcomponents of evidence-accumulation processes (Ratcliff & Rouder, 1998). For both groups, grammar learning was manifested in non-decision parameters, suggesting anticipation of motor responses. For rule-aware participants only, learning also affected bias in evidence accumulation during word reading. These results suggest that implicit grammar learning may be manifested through low-level mechanisms whereas explicit grammar learning may involve more direct engagement with encoded target meanings.

Differences in implicit vs. explicit grammar processing as revealed by drift-diffusion modeling of reaction times

We report the results from two experiments (n=192) examining the congruency effect (better performance for congruent vs incongruent stimuli) for prototype-defined checkerboard composites. We used a complete matching task design as that used to study a robust index of face recognition i.e., the composite face effect. The results from both experiments reveal an effect of order of presentation for congruent and incongruent trials. Critically, participants presented with incongruent first and then congruent trials revealed a significant congruency effect. In contrast, participants presented with congruent first and then incongruent trials showed no congruency effect. These results contribute to the composite effect literature by reporting the first evidence of a congruency effect for artificial non-face stimuli which do not have a predefined orientation. Also, they provide evidence in support of test order as a determining factor potentially modulating the composite effect.

Using prototype-defined checkerboards to investigate the mechanisms contributing to the Composite Face Effect

Experimental design and computational modelling across the cognitive sciences often rely on measures of semantic similarity between words/concepts. Traditional measures of semantic similarity typically rely on corpus-derived linguistic distributional similarity (e.g. LSA) or distance in taxonomic databases (e.g. WordNet), which are theoretically problematic in their lack of grounding in sensorimotor experience. We present a new measure of sensorimotor similarity between concepts, based on multidimensional comparisons of their experiential strength across 11 perceptual and action-effector dimensions in the Lancaster Sensorimotor norms. We demonstrate that, in modelling human similarity and relatedness judgements, sensorimotor similarity has comparable explanatory power to LSA and WordNet distance, explains variance in human judgements which is missed by other measures, and does so with the advantages of remaining both fully grounded and computationally efficient. We further introduce a web-based tool for easily calculating and visualising sensorimotor similarity between words, featuring coverage of nearly 800 million word pairs.

Sensorimotor similarity: A fully grounded and efficient measure of semantic similarity

People’s active interventions play a key role in causal learning. Past studies have tended to focus on how interventions help people learn relationships where causes are independently sufficient to produce an effect. In reality, however, people can learn different rules governing how multiple causes combine to produce an effect, i.e., different functional forms. These forms are examples of causal overhypotheses—abstract beliefs about causal relationships that are acquired in one situation and transferred to another. Here we present an active "blicket" experiment to study whether and how people learn overhypotheses in an active setting. Our results showed participants can learn disjunctive and conjunctive overhypotheses through active training, as measured in a new disjunctive task. Furthermore, intervening on two objects led to better conjunctive judgments, and complementarily, conjunctive training predicted more objects in future interventions. Overall, these results expand our understanding of how active learning can facilitate causal inference.

Exploring Causal Overhypotheses in Active Learning

Recent studies have found that people are sensitive to the large-scale network structure of semantic free associations. The current work aims to conduct a stronger test of people’s sensitivity to structural nuances within the semantic network by going beyond measurements of path lengths between word pairs (e.g., Kumar et al., 2019). Here we examine the influence of distance entropy on semantic priming. Distance entropy is the entropy of the shortest paths from a target word to all other words in the network. Simulations suggested that nodes with lower distance entropy (i.e., many shortest paths of similar lengths) led to more “democratic” spread of activation overall—with higher median and less variable activation levels among nodes—and hence should be more “effective” primes. However, analyses of Semantic Priming Project data were not conclusive and targeted experiments are needed to further examine the effect of distance entropy on semantic priming.

Investigating the effect of distance entropy on semantic priming

As we navigate through the world, we often leave traces of our actions: a broken branch, a footprint in the mud, a dirty coffee mug at a desk. As observers, these traces enable us to make surprisingly complex social inferences about the actions that may have caused them: what the other person may have been doing, what their likely goals were, and more. But how might a conspicuous lack of evidence prompt this same reasoning? We hypothesize that children use intuitive physics to infer possible prior actions and their outcomes, even in the absence of evidence. In support of this proposal, we found that children readily reconstruct an agent’s actions after observing indirect evidence. Importantly, they are also able to use the difficulty of concealing such evidence to interpret its absence.

What happened here? Children integrate physical reasoning to infer actions from indirect evidence

Recent research has found evidence for implicit theory of mind, suggesting that humans quickly and involuntarily compute the mental states of others. One highly influential task within this literature, known as the Dot Perspective Task (DPT), purports to demonstrate implicit visual-perspective taking within adult subjects. However, some studies, consisting of variations of the DPT, have challenged these findings suggesting that the DPT does not demonstrate genuine perspective taking. Instead, they argue that these results are reflective of simple attentional cueing. Additionally, some researchers have argued that the DPT is sensitive to unintended attentional and intentional factors. We report the preliminary findings of an on-ongoing meta-analysis which analyzes participant-level data from 23 experiments and 1381 individual subjects. We find evidence for both directional cueing and implicit perspective taking within the DPT, although the effects of directional cueing are significantly larger. Additionally, we find that the effects of perspective taking are sensitive to attentional and intentional factors. These results cast doubt upon much of the evidence which has been taken to demonstrate implicit theory of mind. At the same time, they suggest that future work may utilize a carefully controlled version of the DPT in order to measure genuine implicit theory of mind more accurately.

Do you see what I see? A meta-analysis of the Dot Perspective Task

Impressions of others’ moral character are key to our social lives, but we rarely directly witness immoral acts, and rather rely on the stories we hear. This creates significant opportunities for narrators to distort their stories in an effort to appear more moral. How does the detection of such persuasion goals affect readers' impressions of the authors' character? Participants read autobiographical stories written by other participants about morally questionable actions they did – written once with no goal, and then again with the goal of appearing morally good or bad. Readers were very accurate in detecting the authors’ goals, but these were nonetheless effective in modulating character impressions. Critically, this effect vanished when readers thought the author didn't care about communicating information accurately. This suggests that audiences sometimes fail to discount narrators' goals when evaluating their character, but only when goals don't come at the cost of communicating information accurately.

I see where you are going: Perception of persuasion goals in moral narratives influences character impressions

Artificial systems currently outperform humans in diverse computational domains, but none has achieved parity in speed and overall versatility of mastering novel tasks. A critical component to human success, in this regard, is the ability to redeploy and redirect data passed between cognitive subsystems (via abstract feature representations) in response to changing task demands. However, analyzing shared representations is difficult in neural systems with distributed nonlinear coding. This work presents a simple but effective approach to this problem. In experiments, the proposed model robustly predicts behavior and performance of multitasking networks on natural language data (MNIST) using common deep network architectures. Consistent with existing theory in cognitive control, representation structure varies in response to (a) environmental pressures for representation sharing, (b) demands for parallel processing capacity, and (c) tolerance for crosstalk. Implications for geometric (dimension, curvature), functional (automaticity, generalizability, modularity), and applied aspects of representation learning are discussed.

Downloads

Next from CogSci 2021

Effects of articulatory suppression on the homophone judgments of Chinese-character words

Similar lecture

HapticCap: A Multimodal Dataset and Task for Understanding User Experience of Vibration Haptic Signals