Papers by Mengyue Wang

6 papers
CreativeBench: Benchmarking and Enhancing Machine Creativity via Self-Evolving Challenges (2026.findings-acl)

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Challenge: Increasing saturation of web data limits further scaling of model intelligence.
Approach: They propose a benchmark to evaluate machine creativity in code generation that combines combinatorial and exploratory creativity through reverse engineering and self-play.
Outcome: The proposed benchmark targets combinatorial and exploratory creativity through reverse engineering and self-play.
Phonetic and Lexical Discovery of Canine Vocalization (2024.findings-emnlp)

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Challenge: Existing methods to study animal language systems rely on human prior knowledge on limited data.
Approach: They propose a self-supervised approach that enables the accurate classification of phones and an adaptive grammar induction method that identifies phone sequence patterns that suggest a preliminary vocabulary within dog vocalizations.
Outcome: The proposed approach breaks the barrier existing approaches relying on human prior knowledge on limited data.
Toward Automatic Discovery of a Canine Phonetic Alphabet (2025.acl-long)

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Challenge: a new algorithm for vocalization communication between dogs is being developed . phonetic units alone are not sufficient to constitute a "language"
Approach: They propose an algorithm that produces a complete alphabet of distinct canine phonemes . the algorithm is expected to function on canines and other animal species .
Outcome: The proposed algorithm produces a complete alphabet of distinct canine phoneme-like units . it is expected to work on canines and other animal species .
METok: Multi-Stage Event-based Token Compression for Efficient Long Video Understanding (2025.emnlp-main)

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Challenge: Recent advances in Video Large Language Models (VLLMs) have significantly enhanced their ability to understand video content.
Approach: They propose a training-free, Multi-stage Event-based Token compression framework that eliminates redundant visual tokens across three critical stages .
Outcome: The proposed framework reduces FLOPs and KV Cache memory consumption while maintaining comparable or even superior accuracy.
D4: a Chinese Dialogue Dataset for Depression-Diagnosis-Oriented Chat (2022.emnlp-main)

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Challenge: Existing human-machine dialogue systems are not able to provide diagnostic information for depression diagnosis due to stigma associated with mental illness.
Approach: They propose to construct a Chinese Dialogue Dataset for depression-diagnosis-oriented chat based on clinical depression diagnostic criteria.
Outcome: The proposed system can be used to diagnose depression using a Chinese Dialogue Dataset.
Mapping Long-term Causalities in Psychiatric Symptomatology and Life Events from Social Media (2024.naacl-long)

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Challenge: Existing studies focus on the semantic content of social media posts, overlooking the evolving nature of mental disorders and symptoms.
Approach: They extract causality between psychiatric symptoms and life events from social media posts and extract temporal attributes to improve diagnosis and treatment planning.
Outcome: The extracted causality features improve diagnostic and treatment planning and improve performance in tasks such as depression and diagnosis point detection.

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