Papers with Cognitive Modeling
The ACQDIV Corpus Database and Aggregation Pipeline (2020.lrec-1)
Copied to clipboard
| Challenge: | ACQDIV corpus database and aggregation pipeline aims to identify universal cognitive processes that allow children to acquire any language. |
| Approach: | They present the ACQDIV corpus database and aggregation pipeline . the tool aims to identify universal cognitive processes that allow children to acquire any language . |
| Outcome: | The ACQDIV corpus database and aggregation pipeline is a tool developed by the European Research Council . the database represents 15 corpora from 14 typologically maximally diverse languages . |
Design of BCCWJ-EEG: Balanced Corpus with Human Electroencephalography (2020.lrec-1)
Copied to clipboard
| Challenge: | Recent research has focused on the fusion of NLP and neuroscience of language. |
| Approach: | They propose to use a balanced corpus of written Japanese (BCCWJ) annotated with human electroencephalography to improve annotations and annotations. |
| Outcome: | The proposed language resource is annotated with human electroencephalography (EEG) and can improve on annotations, genres, languages, etc. |
Evaluating a Century of Progress on the Cognitive Science of Adjective Ordering (2023.tacl-1)
Copied to clipboard
| Challenge: | a new study examines the performance of cognitive hypotheses for adjective ordering in 32 languages . linguists and cognitive scientists have proposed an array of hypothese predicting adjective ordering . |
| Approach: | They compare the combined performance of existing adjective ordering proposals across 32 languages . they propose to use a baseline that reflects random chance accuracy and a higher baseline that measures idealized order . |
| Outcome: | The proposed hypotheses are compared with baselines in 32 languages and with random and idealized baselines. |
ReContraster: Making Your Posters Stand Out with Regional Contrast (2026.acl-long)
Copied to clipboard
| Challenge: | Effective poster design requires rapidly capturing attention and clearly conveying messages. |
| Approach: | They propose a poster-based model that leverages regional contrast to make posters stand out. |
| Outcome: | The proposed model outperforms state-of-the-art methods in producing striking posters. |
AgentGC: Evolutionary Learning-based Lossless Compression for Genomics Data with LLM-driven Multiple Agent (2026.findings-acl)
Copied to clipboard
Sun Hui, Ding Yanfeng, Huidong Ma, Chang Xu, Keyan Jin, Lizheng Zu, Cheng Zhong, Xiaoguang Liu, Gang Wang, Wentong Cai
| Challenge: | Lossless compression has made significant advancements in Genomics Data storage, sharing and management. |
| Approach: | They propose a novel agent-based GD Compressor with 3 layers with a multi-agent named Leader and Worker. |
| Outcome: | The proposed method improves on existing methods with low-level modeling and limited adaptability and user-unfriendly interface. |
Identification and Analysis of Personification in Hungarian: The PerSECorp project (2022.lrec-1)
Copied to clipboard
| Challenge: | despite recent findings on the conceptual and linguistic organization of personification, we have relatively little knowledge about its lexical patterns and grammatical templates. |
| Approach: | They propose a corpus-driven approach to personification analysis in cognitive linguistics . they use a semi-automatically processed corpus to annotate personifying linguistic structures . |
| Outcome: | The proposed method consists of annotating a semi-automatic corpus of car reviews in Hungarian . the corpus is structured and annotated manually, and gives an overview of possible data types . |
Supporting Cognitive and Emotional Empathic Writing of Students (2021.acl-long)
Copied to clipboard
| Challenge: | Empathy skills are an elementary skill in society for daily interaction and professional communication and are therefore elementary for educational curricula. |
| Approach: | They propose an annotation approach to capture emotional and cognitive empathy in student-written peer reviews on business models in germany. |
| Outcome: | The proposed annotation scheme guides annotators to a substantial to moderate agreement with the model and shows that it is effective. |
Recent advances in neural metaphor processing: A linguistic, cognitive and social perspective (2021.naacl-main)
Copied to clipboard
| Challenge: | Metaphor processing systems have benefited from recent studies on the role of metaphor in communication and deep learning for natural language processing. |
| Approach: | They present a review of automated metaphor processing and discuss their results from downstream NLP tasks. |
| Outcome: | The proposed system is based on the findings of a systematic and comprehensive survey of metaphor processing systems published five years ago. |
A Unified Framework for Synaesthesia Analysis (2023.findings-emnlp)
Copied to clipboard
| Challenge: | Synaesthesia is a cognitive phenomenon structuring human thought and action, which makes understanding it challenging. |
| Approach: | They propose a framework for annotating synaesthetic elements and exploring their relationship . they propose to include sensory modalities, cues and stimuli in the framework . |
| Outcome: | The proposed framework yields state-of-the-art results, demonstrating its effectiveness. |
Cascading Biases: Investigating the Effect of Heuristic Annotation Strategies on Data and Models (2022.emnlp-main)
Copied to clipboard
| Challenge: | Cognitive psychologists have documented that humans use cognitive heuristics to make quick decisions while expending less effort. |
| Approach: | They propose tracking annotator heuristic traces where they measure low-effort annotation strategies that could indicate usage of various cognitive heurs. |
| Outcome: | The proposed tracking annotator heuristic traces shows that annotators are using multiple cognitive heurs based on psychological tests. |
Language (Re)modelling: Towards Embodied Language Understanding (2020.acl-main)
Copied to clipboard
| Challenge: | Despite the rapid progress in NLU, current systems lack the rich mental representations that people use for language understanding. |
| Approach: | They propose an approach to representation and learning based on the tenets of embodied cognitive linguistics (ECL) they propose a system architecture along with a roadmap towards realizing this vision. |
| Outcome: | The proposed approach will improve the performance of existing systems and provide a roadmap towards realizing this vision. |
PRISM: Probabilistic Reward Model with Inherent Structural Modeling (2026.acl-long)
Copied to clipboard
| Challenge: | Existing evaluators compress diverse human judgments into a single scalar, leading to brittle alignment and reward hacking. |
| Approach: | They propose a Gaussian-based reinterpretation of reward evaluation as a conditional distribution and a mixture of Gaussians to capture conflicting preference dimensions. |
| Outcome: | The proposed model outperforms scalar baselines in accuracy and generalization. |
Cognitive Linguistic Identity Fusion Score (CLIFS): A Scalable Cognition‐Informed Approach to Quantifying Identity Fusion from Text (2025.emnlp-main)
Copied to clipboard
| Challenge: | Existing methods for measuring identity fusion are limited and require controlled surveys or direct field contact. |
| Approach: | They propose a new metric that integrates cognitive linguistics with large language models to measure identity fusion. |
| Outcome: | The proposed metric outperforms existing methods and human annotations in violence risk assessment. |
InteRead: An Eye Tracking Dataset of Interrupted Reading (2024.lrec-main)
Copied to clipboard
| Challenge: | Eye movements during reading can provide insights into cognitive processes and language comprehension, but the scarcity of reading data with interruptions hampers advances in the development of intelligent learning technologies. |
| Approach: | They propose a dataset of eye movements during reading that includes eye movements and word frequency effects. |
| Outcome: | The proposed dataset shows that interruptions, word length and word frequency effects significantly impact eye movements during reading. |
VisEscape: A Benchmark for Evaluating Exploration-driven Decision-making in Virtual Escape Rooms (2025.emnlp-main)
Copied to clipboard
| Challenge: | Existing studies on embodied agents have addressed the importance of exploration in environments where tasks and solutions are not predefined. |
| Approach: | They propose a virtual escape room that evaluates AI models in a dynamic environment . they propose to integrate memory management and reasoning into the simulation . |
| Outcome: | The proposed model improves in dynamic and exploration-driven environments by integrating memory management and reasoning. |
UniDebugger: Hierarchical Multi-Agent Framework for Unified Software Debugging (2025.emnlp-main)
Copied to clipboard
Cheryl Lee, Chunqiu Steven Xia, Longji Yang, Jen-tse Huang, Zhouruixing Zhu, Lingming Zhang, Michael R. Lyu
| Challenge: | Existing LLMs focus on isolated steps and struggle with complex bugs. |
| Approach: | They propose a framework for unified debugging through multi-agent synergy . it mimics the entire cognitive processes of developers with each agent specialized as a particular component of this process . |
| Outcome: | The proposed framework outperforms state-of-the-art methods on repo-level benchmarks. |
CARE-CR: Context-Aware Routing and Expert Fusion for Multi-Preference Cognitive Restructuring (2026.findings-acl)
Copied to clipboard
| Challenge: | Large Language Models (LLMs) offer promising avenues for automated cognitive restructuring in mental health settings, but current approaches lack the adaptability to balance conflicting therapeutic dimensions, such as empathy and rationality. |
| Approach: | They propose a decoupled optimization framework that implements a dimension-guided Monte Carlo tree search to train expert policies specialized for distinct therapeutic attributes rather than relying on a monolithic alignment strategy. |
| Outcome: | The proposed framework achieves consistent improvements over baselines across multiple evaluation dimensions, including diagnostic accuracy, contextual appropriateness, task effectiveness, and overall helpfulness, while enabling controllable cognitive restructuring generation. |
SceneGram: Conceptualizing and Describing Tangrams in Scene Context (2025.findings-acl)
Copied to clipboard
| Challenge: | Current systems show mixed results in reproducing human variation in object naming . figurative descriptions for abstract stimuli remain a major challenge in vision and language research . |
| Approach: | They propose to analyze human references to tangrams placed in different scene contexts . they analyze the richness and variability of conceptualizations found in human references . |
| Outcome: | The proposed model does not account for the richness and variability of human references. |
Can LLMs Estimate Student Struggles? Human-AI Difficulty Alignment with Proficiency Simulation for Item Difficulty Prediction (2026.findings-acl)
Copied to clipboard
| Challenge: | Accurate estimation of item (question or task) difficulty suffers from the cold start problem. |
| Approach: | They propose to use large-scale empirical analysis to examine human-AI Difficulty Alignment . they find that models struggle to simulate the capability limitations of students . |
| Outcome: | The proposed model size is not reliably helpful for human-AI alignment . high performance often impedes accurate difficulty estimation, the authors say . |