Papers with CR
On the Influence of Coreference Resolution on Word Embeddings in Lexical-semantic Evaluation Tasks (2020.lrec-1)
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| Challenge: | Existing word embeddings rely on local information delimited by context windows or dependency parents to predict word relations. |
| Approach: | They propose to use coreference resolution to find all spans of a text that refer to the same entity to improve the F1-Scores. |
| Outcome: | The proposed methods do not benefit significantly from pronoun substitution. |
Z-coref: Thai Coreference and Zero Pronoun Resolution (2024.acl-srw)
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| Challenge: | limited research and datasets pose significant challenges in Thai language . a proposed model capable of simultaneously handling CR and ZPR tasks takes less time to train . |
| Approach: | They propose to annotate a Thai-based CR and ZPR dataset and introduce a model that can handle both tasks by adjusting the span definition to include token gaps. |
| Outcome: | The proposed model outperforms the state-of-the-art in resolving both coreference resolution and zero-pronoun resolution while taking less time to train. |
CausalEval: Towards Better Causal Reasoning in Language Models (2025.naacl-long)
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Longxuan Yu, Delin Chen, Siheng Xiong, Qingyang Wu, Dawei Li, Zhikai Chen, Xiaoze Liu, Liangming Pan
| Challenge: | Large language models (LLMs) have been used for a variety of tasks, including problem-solving, decision-making, and understanding of the world. |
| Approach: | They propose a review of existing methods aimed at enhancing LMs for causal reasoning . they categorize existing methods as reasoning engines or as helpers providing knowledge or data to traditional methods . |
| Outcome: | The proposed methods perform better than existing methods on a range of tasks. |
ASTRID - An Automated and Scalable TRIaD for the Evaluation of RAG-based Clinical Question Answering Systems (2025.findings-acl)
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| Challenge: | Current automated RAG metrics perform poorly in clinical and conversational use cases. |
| Approach: | They propose an automated and scaleable TRIaD for evaluating clinical QA systems leveraging Retrieval Augmented Generation (RAG) metric consisting of three metrics: Context Relevance (CR), Refusal Accuracy (RA), and Conversational Faithfulness (CF). |
| Outcome: | The proposed metric captures the faithfulness of a model’s response without penalising conversational elements and captures refusal to address questions outside of the system’s scope of practice. |
Revisiting Commonsense Reasoning in Machine Translation: Training, Evaluation and Challenge (2023.acl-long)
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| Challenge: | CR is the ability to understand and navigate the world using basic knowledge and understanding shared by most people. |
| Approach: | They propose to incorporate pretrained knowledge into NMT models and use them as robust testbeds for investigating CR in NMT. |
| Outcome: | The proposed method improves the training of NMT models with high CR abilities and provides accurate evaluation metrics. |
Challenges to Evaluating the Generalization of Coreference Resolution Models: A Measurement Modeling Perspective (2024.findings-acl)
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| Challenge: | a recent study shows that evaluations of CR models on multiple datasets conflate different factors concerning what is being measured. |
| Approach: | They propose to view evaluations through the lens of measurement modeling . they show that evaluations risk conflating different factors concerning what is being measured . |
| Outcome: | The evaluations on seven datasets show that models that reflect coreference generalization are often correlated with differences in how coreference is defined and operationalized. |
Crisp: Cognitive Restructuring of Negative Thoughts through Multi-turn Supportive Dialogues (2025.emnlp-main)
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Jinfeng Zhou, Yuxuan Chen, Jianing Yin, Yongkang Huang, Yihan Shi, Xikun Zhang, Libiao Peng, Rongsheng Zhang, Tangjie Lv, Zhipeng Hu, Hongning Wang, Minlie Huang
| Challenge: | Existing approaches to cognitive restructuring (CR) are limited by entrenched cognitive distortions, emotional resistance, and individual differences. |
| Approach: | They propose a framework that structures CR as theory-grounded multi-stage multi-turn dialogue and a multi-channel loop mechanism to account for diverse individual distortions. |
| Outcome: | The proposed framework integrates supportive strategies for emotional management and a multi-channel loop mechanism to account for diverse individual distortions. |