Papers with American
Augmenting Poetry Composition with Verse by Verse (2022.naacl-industry)
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| Challenge: | a new approach to poetry generation has been developed that allows an AI to generate a full poem by itself, thus writing in a closed system. |
| Approach: | They describe an AI poet that offers suggestions while a user is composing a poem . they use a generative model and a dual encoder model to offer the suggestions . |
| Outcome: | The proposed system can offer suggestions generated lines of verse while a user is composing a poem. |
SLENDER: Structured Outputs for SLM-based NER in Low-Resource Englishes (2025.acl-industry)
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| Challenge: | Named Entity Recognition (NER) for low-resource variants of English remains challenging, as most models are trained on datasets predominantly focused on American or British English. |
| Approach: | They propose a new output format for Named Entity Recognition (NER) that achieves a three-fold reduction in inference time compared to JSON format. |
| Outcome: | The proposed output format achieves a three-fold reduction in inference time on average compared to JSON format, which is widely used for structured outputs. |
Machine Translation between Spoken Languages and Signed Languages Represented in SignWriting (2023.findings-eacl)
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| Challenge: | Yin et al. ( 2021) calls for including sign language processing (SLP) in natural language processing research. |
| Approach: | They propose to use a sign language writing system to parse, factorize, decode and evaluate signed languages. |
| Outcome: | The proposed method achieves over 30 BLEU in a bilingual setup and over 20 BLUE in two multilingual setups. |
GeoMLAMA: Geo-Diverse Commonsense Probing on Multilingual Pre-Trained Language Models (2022.emnlp-main)
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| Challenge: | Recent work shows that Pre-trained Language Models store relational knowledge and utilize it for performing downstream tasks. |
| Approach: | They propose a benchmark dataset for probing the diversity of relational knowledge in multilingual PLMs. |
| Outcome: | The proposed dataset contains 3125 prompts in English, Chinese, Hindi, Persian, and Swahili . larger multilingual PLMs variants do not store geo-diverse concepts better than its smaller variant . |
OpenHands: Making Sign Language Recognition Accessible with Pose-based Pretrained Models across Languages (2022.acl-long)
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| Challenge: | a new study examines the performance of pretraining for sign language recognition in low-resource settings. |
| Approach: | They propose using pose extracted through pretrained models as the standard modality of data to reduce training time and enable efficient inference. |
| Outcome: | The proposed model reduces training time and allows efficient inference in sign languages. |
ChiSense-12: An English Sense-Annotated Child-Directed Speech Corpus (2022.lrec-1)
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| Challenge: | Recent evidence suggests that the speech children hear early in development is rich in word sense ambiguity, and also that children's early vocabularies are populated by ambiguous words. |
| Approach: | They sense-tagged 53 corpora of American and English speech directed to 958 target children up to 59 months of age and selected target senses that they know young children understand. |
| Outcome: | The sense-tagged corpus ChiSense-12 was used to examine the role of verb-event structure in child word sense disambiguation. |
Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede’s Cultural Dimensions (2025.coling-main)
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| Challenge: | Large language models (LLMs) are deployed in many countries, but they fail to account for cultural variances among their potential users. |
| Approach: | They propose to use Hofstede’s cultural dimension framework to quantify cultural alignment using latent variable analysis to evaluate large language models against cultural dimensions of regions like the United States, China, and Arab countries. |
| Outcome: | The proposed model is compared against LLMs in the United States, China, and Arab countries and demonstrates that all models struggle to grasp cultural values, while GPT-4 shows a unique capability to adapt to cultural nuances, particularly in Chinese settings. |
FACTIFY3M: A benchmark for multimodal fact verification with explainability through 5W Question-Answering (2023.emnlp-main)
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Megha Chakraborty, Khushbu Pahwa, Anku Rani, Shreyas Chatterjee, Dwip Dalal, Harshit Dave, Ritvik G, Preethi Gurumurthy, Adarsh Mahor, Samahriti Mukherjee, Aditya Pakala, Ishan Paul, Janvita Reddy, Arghya Sarkar, Kinjal Sensharma, Aman Chadha, Amit Sheth, Amitava Das
| Challenge: | Disinformation can cause disruption in the share market, panic and anxiety in society, and even death during crises. |
| Approach: | a new dataset is being developed to help combat disinformation . the dataset is a multimodal fake news dataset with 5W question-answering . |
| Outcome: | FACTIFY 3M is the largest dataset and benchmark for multimodal fact verification. |
MAUD: An Expert-Annotated Legal NLP Dataset for Merger Agreement Understanding (2023.emnlp-main)
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Steven Wang, Antoine Scardigli, Leonard Tang, Wei Chen, Dmitry Levkin, Anya Chen, Spencer Ball, Thomas Woodside, Oliver Zhang, Dan Hendrycks
| Challenge: | Merger Agreement Understanding Dataset (MAUD) is an expert-annotated reading comprehension dataset based on the American Bar Association's 2021 Public Target Deal Points Study. |
| Approach: | They propose a Merger Agreement Understanding Dataset with over 39,000 examples and over 47,000 annotations. |
| Outcome: | The Merger Agreement Understanding Dataset (MAUD) is an expert-annotated reading comprehension dataset based on the American Bar Association's 2021 Public Target Deal Points Study. |
Can Small Vision–Language Models Perform Sign Language Translation? (2026.findings-acl)
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| Challenge: | Vision-Language Models (VLMs) have shown strong generalization across multimodal tasks, but their capacity to handle sign language translation (SLT) remains unclear. |
| Approach: | They propose entity- and semantics-aware metrics tailored for SLT to evaluate their performance. |
| Outcome: | The proposed metrics highlight the limitations of general-purpose VLMs to SLT, unlike their applicability in other tasks. |