Netherlands

Chain-of-Thought (CoT) has brought a fresh perspective to improve the reasoning ability of large language models (LLMs). To relieve the burden of manual design in CoT, Zero-shot CoT has pioneered a direct interaction with LLMs. Based on it, researchers attempt to optimize reasoning paths through various prompting approaches like reflection, selection, and planning. However, few studies have focused on the possibility of combining all these strategies through a cognitive theory. Inspired by experiential learning, this paper proposes a new zero-shot prompting method based on Kolb&#39;s reflective cycle, named Self-Hint prompting. Specifically, Self-Hint prompting introduces an automated iterative interaction approach to simulate the conscious reflection process, which uses intermediate observations as hints to guide LLMs. We have conducted comprehensive experiments on various math reasoning benchmarks. The empirical results on GPT models demonstrate the effectiveness of our method. Proposed Self-Hint prompting consistently outperforms other zero-shot baselines.

**Authors:**

Jindou Chen: Shanghai Jiao Tong University; Jidong Tian: Shanghai Jiao Tong University; Yaohui Jin: Artificial Intelligence Institute

CogSci 2024

Self-Hint Prompting Improves Zero-shot Reasoning in Large Language Models via Reflective Cycle

### Welcome to ACL 2023, the 61st Annual Meeting of the Association for Computational Linguistics! 
 The conference will be held in Toronto, Canada, July 9-14, 2023. 
Following the succession of the recent conferences in our field, ACL 2023 will adopt a hybrid format.
While the impact of Covid has considerably diminished in terms of traveling, obtaining visas to Canada
entails a very long process. Moreover, the global economic conditions pose challenges for many individuals to travel to conferences. Recognizing these circumstances, we know many participants may not be
able to attend the conference in person. Therefore, we are committed to providing a great virtual platform
so everyone has the opportunity to interact with other participants and enjoy the conference. Based on the
current registered participants, approxiately 30% have chosen to attend the conference virtually. Whether
you join us in person or virtually, we sincerely hope everyone has a remarkable conference experience. 
This General Chair’s message is where I express my gratitude to the many individuals who have made
enormous contributions to the conference over the past year.

Read [**ACL 2023 General Chair's message**](https://docs.google.com/document/d/1WobYM7norbG4dI48s75HfJoD89qgX5a_F-6U8AteLSA/edit?usp=sharing/) in full.

##### **[Conference Handbook](https://2023.aclweb.org/downloads/acl2023-handbook.pdf)**

ACL 2023

The Association for Computational Linguistics (ACL) is the premier international scientific and professional society for people working on computational problems involving human language, a field often referred to as either computational linguistics or natural language processing.

Chain-of-Thought (CoT) has brought a fresh perspective to improve the reasoning ability of large language models (LLMs). To relieve the burden of manual design in CoT, Zero-shot CoT has pioneered a direct interaction with LLMs. Based on it, researchers attempt to optimize reasoning paths through various prompting approaches like reflection, selection, and planning. However, few studies have focused on the possibility of combining all these strategies through a cognitive theory. Inspired by experiential learning, this paper proposes a new zero-shot prompting method based on Kolb's reflective cycle, named Self-Hint prompting. Specifically, Self-Hint prompting introduces an automated iterative interaction approach to simulate the conscious reflection process, which uses intermediate observations as hints to guide LLMs. We have conducted comprehensive experiments on various math reasoning benchmarks. The empirical results on GPT models demonstrate the effectiveness of our method. Proposed Self-Hint prompting consistently outperforms other zero-shot baselines.

**Authors:**

Jindou Chen: Shanghai Jiao Tong University; Jidong Tian: Shanghai Jiao Tong University; Yaohui Jin: Artificial Intelligence Institute

poster

The 46th Annual Meeting of the Cognitive Science Society was an in-person meeting held in Rotterdam, The Netherlands at the Postillion Hotel & Conference Centre.

**ON-DEMAND PROGRAM ACCESS AFTER THE CONFERENCE** 
Recordings of the invited program are now available. You can access them by clicking on the 'Schedule' icon on the left. Select view by week and navigate to the day and time slot of the recording you wish to view. Click on the time slot to access the recording.

Recordings available (click on each recording to view):

**Thursday, July 25** 
0900: [Keynote Speaker Morgan Barense on Enhancing real-world event memory](https://underline.io/events/465/sessions/17997/lecture/99084-dynamics-between-minds-and-the-environment) 
1000: [Gleitman Award Winner Isabelle Dautriche on Language Foundations: Insights from acquisition, communication, cognition, and more](https://underline.io/events/465/sessions/18000/lecture/99085-gleitman-talk) 
1415: [Invited Symposium: Dynamics between minds and the environment](https://underline.io/events/465/sessions?eventSessionId=18016&searchGroup=lecture) 
1700: [Rumelhart Prize Presentation Speaker Alison Gopnik on Exploit, explore, empower: Three ages and three intelligences](https://underline.io/events/465/sessions/18028/lecture/99161-rp1-rumelhart-prize-presentation) 

**Friday, July 26** 
0900: [C.L. de Carvalho-Heineken Prize Keynote Speaker Kia Nobre on Focusing in memory](https://underline.io/events/465/sessions/18035/lecture/99162-hp1-c-l-de-carvalho-heineken-prize-keynote-address) 
1030: [Rumelhart Symposium: Childhood as exploration](https://underline.io/events/465/sessions/18038/lecture/100346-childhood-as-exploration) 
1415: [Elman Prize Symposium](https://underline.io/events/465/sessions?eventSessionId=18053&searchGroup=lecture) 
1600: [Invited Symposium: Dynamics between minds](https://underline.io/events/465/sessions?eventSessionId=18065&searchGroup=lecture) 
1745: [Keynote Speaker Andrea E. Martin on Neural dynamics encode the structure and statistics of language](https://underline.io/events/465/sessions/18077/lecture/99271-neural-dynamics-encode-the-structure-and-statistics-of-language) 

**Saturday, July 27** 
0900: [Keynote Speaker Gregor Schöner on How higher cognition emerges from the dynamics of strongly interacting neural populations](https://underline.io/events/465/sessions/18083/lecture/99273-dynamics-within-the-mind) 
1000: [Glushko Talks](https://underline.io/events/465/sessions?eventSessionId=18086&searchGroup=lecture) 
1500: [Invited Symposium: Dynamics within minds](https://underline.io/events/465/sessions?eventSessionId=18100&searchGroup=lecture) 


#### **CogSci 2024 Program Book**
<div style="position:relative;padding-top:0;width:900px;height:500px;"><iframe style="position:absolute;border:none;width:100%;height:100%;left:0;top:0;" src="https://online.fliphtml5.com/ebtyf/cble/" seamless="seamless" scrolling="no" frameborder="0" allowtransparency="true" allowfullscreen="true" ></iframe></div>


**The Program Book can be downloaded [here](https://drive.google.com/file/d/1yRVp1cBqRnAbdYi4GXWV_pZeyWNsRquv/view?usp=sharing).**

#### **Letter from the President**

Welcome to the 2024 Meeting of the Cognitive Science Society in Rotterdam! CogSci 2024 brings together a large community of cognitive scientists who have traveled here from around the world, as well as a smaller group of remote presenters. I would like to extend an especially warm welcome to our first-time CogSci meeting attendees, and hope that 
their experience inspires them to join our future meetings for many years to come.

I want to thank this year’s conference co-chairs, Larissa K Samuelson, Stefan Frank, Mariya Toneva, Allyson Mackey, and Eliot Hazeltine, for putting together an amazing series of invited talks and symposia around the theme of Dynamics of Cognition. The co-chairs also deserve credit for handling a record-breaking number of submissions and producing a truly exciting conference program 

Beyond the invited talks and symposia dedicated to this year’s conference theme, I would like to highlight the presentations and events honoring the 
Rumelhart, Elman, Gleitman and C .L . de Carvalho Heineken prize winners, including the Rumelhart reception on Thursday. As you may know, we are recording all of the invited talks and symposia, and all prize-winners’ talks, and will be making this content available after the conference. 

The Cognitive Science Society relies on the volunteer efforts of our Governing Board members who work on matters related to our membership; conference policies; diversity and inclusion, international, and outreach initiatives; prizes and much more. We welcome interest from Society members who would like to become more involved in what we do. The 
Society is deeply grateful to Rick Dale and Andrea Bender, who serve as editors of the two Society journals, Cognitive Science and Topics in Cognitive Science respectively. We especially acknowledge our editors’ generosity in donating their stipends each year to D&I and outreach efforts. 

This year’s Annual Meeting depends critically on the support of Marischal De Armond and his team at Podium Conference Specialists: Sharon Zwack, Cendrine De Vis, Sarah-Kate Burke, and Rachel Waller worked tirelessly to secure the venue and handled a multitude of logistical and organizational issues, from arranging coffee breaks and receptions to making sure that a huge number of posters fits comfortably into the available space. Finally, and importantly, I would like to acknowledge the Cognitive Science Society Executive Officer, Erica Wojcik, for managing the complex and ever expanding sphere of our Society’s activities.

I hope you enjoy this year’s meeting and the many different opportunities to engage with the vibrant community of cognitive scientists gathered here. I also hope you get a chance to explore the great city of Rotterdam with its many attractions, museums, restaurants and scenic views. If you’d like to talk more about our Society, or simply want to say hello, please stop by!

![](https://assets.underline.io/markdown_image/1/image/3c66d0e21fff30e204df1138ffd15173.jpeg)

**Anna Papafragou** 
President, Cognitive Science 
Society 2023-2024

**CODE OF CONDUCT** 
By attending the CogSci 2024 Conference, you are required to adhere to the society’s [Code of Conduct](https://drive.google.com/file/d/16-6KkptF0Gn3ZYGJDlpqpwTdImw45Ng0/view?usp=drive_link).

**ABOUT THE COGNITIVE SCIENCE SOCIETY** 
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.

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The 46th Annual Meeting of the Cognitive Science Society presents the latest research across cognitive science and highlights the theme of Cognition in Context.

Drawing on the principles of associative learning theory and positing a statistical foundation for language acquisition, this paper investigates the independent contributions of the predictive validities of verbal and constructional cues in English native and non-native speakers’ mental representations of the English as-predicative construction. This is examined through two experiments: a sentence completion task targeting constructional outcome retrieval (Experiment 1), and a gap-fill schema task with a focus on verb retrieval (Experiment 2). The results demonstrate that both cues are integrated in parallel when eliciting a constructional outcome (Experiment 1), but only construction cue validity plays a role in eliciting verbal outcomes (Experiment 2). Verb frequency and voice additionally contribute to the retrieval of verbal and constructional information in distinct manners. The present study raises discussions about distributional cue integration in forward versus backward retrieval of linguistic information, in addition to emphasizing the importance of considering cross-linguistic factors in future research.

**Authors:**

Ivana Domazetoska: University of Melbourne; Helen Zhao: University of Melbourne

Native and Non-Native Speakers’ Cue Integration in the Processing of the English As-Predicate Construction

A large body of work in psycholinguistics has focused on the idea that online language comprehension can be shallow or `good enough': given constraints on time or available computation, comprehenders may form interpretations of their input that are plausible but inaccurate. However, this idea has not yet been linked with formal theories of computation under resource constraints. Here we use information theory to formulate a model of language comprehension as an optimal trade-off between accuracy and processing depth, formalized as bits of information extracted from the input, which increases with processing time. The model provides a measure of processing effort as the change in processing depth, which we link to EEG signals and reading times. We validate our theory against a large-scale dataset of garden path sentence reading times, and EEG experiments featuring N400, P600 and biphasic ERP effects. By quantifying the timecourse of language processing as it proceeds from shallow to deep, our model provides a unified framework to explain behavioral and neural signatures of language comprehension.

**Authors:**

Jiaxuan Li: University of California Irvine; Richard Futrell: UC Irvine

An information-theoretic model of shallow and deep language comprehension

How can we judge if conversation partners will be good cooperation partners in other tasks? A recent proposal is that low-level linguistic similarity such as subconsciously matching others’ language use may be a signal of cooperativeness. To elucidate the mechanisms behind this relationship, we conducted two experiments, in which we found that conversation partners that matched the participants’ syntax and pitch were perceived as more cooperative and were chosen more often as cooperation partners. Our findings further suggest that the sheer act of adapting to someone’s linguistic production was not as crucial for choosing cooperation partners, even if it involved an initial cognitive investment. Rather, the decisive factor was sharing someone’s linguistic preferences and thereby indicating group membership. This may have important implications for understanding cooperation partner choice and for understanding the (co-)evolution of language and cooperation, which both are traits that are particularly prominent in humans.

**Authors:**

Theresa Matzinger: University of Vienna; Irene Böhm: University of Vienna

The Power of Linguistic Similarity for Unlocking Cooperation - Evidence from Syntax and Pitch Experiments

Large language models are increasingly being used for education and science communication by automatically generating explanations of scientific concepts. However, prior research has found that the analogies produced by LLMs lack human-like psycholinguistic properties important for readability. In this work, we propose cognitive conflict reinforcement learning (CCRL) to improve the psycholinguistic properties of analogies generated by LLMs. Specifically, we create cognitive conflict between the original LLM and a cloned LLM during reinforcement learning. This helps address the cognitive rigidity problem in LLMs. Experimental results demonstrate that our approach significantly outperforms existing RL algorithms and human performance in improving various readability metrics of generated analogies.

**Authors:**

Yuang Cai: Beijing University of Posts and Telecommunications; Yuyu Yuan: Beijing University of Posts and Telecommunications; Jinsheng Shi: Beijing University of Posts and Telecommunications; Rui Han: Beijing University of Posts and Telecommunications; Zhenyu Zhao: Beijing University of Post and Telecommunications ; Zijie Shi: Beijing University of Posts and Telecommunications

Improving the Readability of Scientific Concept Analogies with Cognitive Conflict Reinforcement Learning

In the field of medical decision-making, understanding the treatment intentions of clinicians is crucial for effective treatment strategies. However, these intentions are often implicit and challenging to quantify. In this paper, we propose a novel two-module model to infer and implement clinicians' treatment intentions through treatment records. We construct the InfCTI module, which infers intentions and quantifies them numerically, and the ImpCTI module, which generates treatment strategies based on inferred intentions. Our experiments demonstrate that the treatment strategies obtained by ImpCTI reflect clinicians' intentions and the intention values obtained by InfCTI are reasonable. This model has the potential to improve the quality of care provided to patients.

**Authors:**

Jinsheng Shi: Beijing University of Posts and Telecommunications; Yuyu Yuan: Beijing University of Posts and Telecommunications; Yuang Cai: Beijing University of Posts and Telecommunications; Rui Han: Beijing University of Posts and Telecommunications; Zhenyu Zhao: Beijing University of Post and Telecommunications ; Zijie Shi: Beijing University of Posts and Telecommunications

InfCTI-ImpCTI: Inferring and Implementing Clinicians' Treatment Intentions

Behavioral studies and computer simulations of analogical retrieval suggest that the availability of surface matches in long-term memory (LTM) hinders the spontaneous retrieval of purely structural analogs. We investigated whether this competition effect still holds during hypothesis-generation, a goal-driven activity that entails a more profound and sustained consideration of the target situation. In two experiments, we obtained that the availability of a less isomorphic but more superficially similar item did not complicate retrieving a structural analog, thus suggesting that goal-driven activities such as hypothesis generation aid participants in overcoming the activation of a structurally suboptimal analog in working memory, as compared to pragmatically impoverished activities such as reading the target situation. However, the activation of the surface match hindered the successful application of structural matches that were successfully retrieved. Results render a more nuanced picture of the role of surface similarities in analogical thinking, traditionally restricted to the retrieval stage.

**Authors:**

Sabina Leon: Agencia Nacional de Promoción Científica y Tecnológica (ANPCyT); Leandro E. Rivas: University of Comahue; Maximo Trench: University of Comahue

Analogical Reasoning During Hypothesis Generation: The Role of Surface Competition During Access and Transfer

Social media has affected how we relate to our body image. Digital makeovers have both reinforced existing beauty ideals and created new ones. This project investigated whether young adults’ detection of image filters was biased by internalized beauty ideals and gender. Participants completed a visual detection task (forced choice paradigm) where contrast filter correction was assessed for images of male and female bodies that were thin, average, and curvaceous/muscular. Results showed that people can detect filters and that accuracy is higher when filters are applied to bodies that represent the historical beauty ideals: thin female bodies and muscular male bodies. These findings suggest that the perception of low-level image features is biased to fit internalized beliefs about beauty

**Authors:**

Ivonnia M Flores Bravo: National Scientific and Technological Council of Argentina; Trinidad Belén Speranza: Centro de Investigaciones en Psicología y Psicopedagogía. National Scientific Research and Technology Council; Gaston Saux: Centro de Investigaciones en Psicología y Psicopedagogía, Pontificia Universidad Católica Argentina; Verónica Ramenzoni: Centro de Investigaciones en Psicología y Psicopedagogía. National Scientific Research and Technology Council

Detection of Image Filters is Biased by Gender and Internalized Beauty Ideals

Human cognition significantly influences expressed behavior and is intrinsically tied to authentic personality traits. Personality assessment plays a pivotal role in various fields, including psychology, education, social media, etc. However, traditional self-report questionnaires can only provide data based on what individuals are willing and able to disclose, thereby lacking objective. Moreover, automated measurements and peer assessments demand significant human effort and resources. In this paper, given the advantages of the Virtual Reality (VR) technique, we develop a VR simulator --- PersonalityScanner, to stimulate cognitive processes and simulate daily behaviors based on an immersive and interactive simulation environment, in which participants carry out a battery of engaging tasks that formulate a natural story of first-day at work. Through this simulator, we collect a synchronous multi-modal dataset with ten modalities, including first/third-person video, audio, text, eye tracking, facial microexpression, pose, depth data, log, and inertial measurement unit. By systematically examining the contributions of different modalities on revealing personality, we demonstrate the superior performance and effectiveness of PersonalityScanner.

**Authors:**

Xintong Zhang: Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University; Di Lu: Peking University; Huiqi Hu: Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University; Nan Jiang: Peking University; Xianhao Yu: Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University; Jinan Xu: Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University; Yujia Peng: Peking University; Qing Li: National Key Laboratory of Beijing Institute for General Artificial Intelligence; Wenjuan Han: Beijing Key Lab of Traffic Data Analysis and Mining, Beijing Jiaotong University

PersonalityScanner: Exploring the Validity of Personality Assessment Based on Multimodal Signals in Virtual Reality

Adult language learners have difficulty segmenting words from continuous speech when the phonology is unfamiliar. Since speaker variability is known to improve acquisition of novel language structures, it could be processed in ways that bootstrap phonological patterns and enhance learners’ ability to segment words. To test this, the present experiment examined adult participants’ learning of a stream of statistically determined tri-syllabic words that were spoken by one or multiple speakers. Syllables were constructed with either English phonology or non-English phonology. Two tasks (target detection and two-alternative forced choice) assessed the extent of listeners’ sensitivity to language patterns and word segmentation. Results suggest speaker variability negatively impacted learners’ ability to track the underlying statistics. 2AFC word segmentation performance was poor—independent of speaker number; it is hypothesized that attentional demands of the target detection task conflicted with statistical word segmentation mechanisms.

**Authors:**

Larissa Melville: University of British Columbia; Alexis K. Black: The University of British Columbia

Beyond Noise: The Role of Speaker Variability on Statistical Learning

Studies have shown that readers who do not always experience an inner reading voice (less-IRV readers) move their eyes more freely and do more efficient silent reading than those who always experience IRV (full-IRV readers). This conclusion suggests that less-IRV readers may not be suited for studying with vocalization. In this study, forty students were assigned to full- and less-IRV reading groups. The main task in the experiment was to read short stories and answer comprehension tests. The reading materials comprised 12 stories, the same as those used by Morita and Takahashi (2019). Participants read them with audio assistance and answered three comprehension tests after reading each story. While reading the stories, the readers' eye movements were recorded. The results of the eye-movement index showed no difference in eye movement patterns (fixation, fixation time, saccade size, regression) and comprehension between the two kinds of readers. We found no relationship between inner reading voice styles and eye movements in audio-assisted reading.

**Authors:**

Yefei Liang: Hiroshima University; Takumi Arima: Hiroshima University; Aiko Morita: Hiroshima University

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