Papers with progressive tasks

3 papers
An End-to-End Progressive Multi-Task Learning Framework for Medical Named Entity Recognition and Normalization (2021.acl-long)

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Challenge: Existing models for medical named entity recognition and named entity normalization suffer from error propagation between the two tasks.
Approach: They propose an end-to-end progressive multi-task learning model for jointly modeling medical named entity recognition and normalization in an effective way.
Outcome: The proposed model reduces error propagation by exploiting the learnable features for both tasks to improve performance.
PunMemeCN: A Benchmark to Explore Vision-Language Models’ Understanding of Chinese Pun Memes (2025.emnlp-main)

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Challenge: Pun memes combine wordplay with visual elements to create humor, irony, or other rhetorical effects.
Approach: They propose a benchmark to assess Chinese pun memes' processing capabilities across three progressive tasks: pun meme detection, sentiment analysis, and chat-driven meme response.
Outcome: The proposed model can detect pun memes, analyze sentiments, and respond to chats, while ignoring homophone wordplay.
LongTutor: Benchmarking Large Language Models for Long-term Personalized Tutoring (2026.acl-long)

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Challenge: Existing evaluations focus on isolated, short-term interactions, overlooking the inherently long-term nature of learning.
Approach: They propose a benchmark for long-term personalized tutoring based on an annotated learning log . they propose an automated generator–verifier pipeline to enable benchmark expansion .
Outcome: The proposed benchmarks evaluate LLMs across three progressive tasks: evidence acquisition, knowledge state diagnosis, and adaptive teaching action.

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