bibtex_url stringlengths 41 50 | bibtext stringlengths 693 2.88k | abstract stringlengths 0 2k | authors listlengths 1 45 | title stringlengths 21 206 | id stringlengths 7 16 | type stringclasses 2
values | arxiv_id stringlengths 9 12 ⌀ |
|---|---|---|---|---|---|---|---|
https://aclanthology.org/2024.findings-acl.968.bib | @inproceedings{yue-etal-2024-fragrel,
title = "{F}rag{R}el: Exploiting Fragment-level Relations in the External Memory of Large Language Models",
author = "Yue, Xihang and
Zhu, Linchao and
Yang, Yi",
editor = "Ku, Lun-Wei and
Martins, Andre and
Srikumar, Vivek",
booktitle = "... | To process contexts with unlimited length using Large Language Models (LLMs), recent studies explore hierarchically managing the long text. Only several text fragments are taken from the external memory and passed into the temporary working memory, i.e., LLM{'}s context window. However, existing approaches isolatedly h... | [
"Yue, Xihang",
"Zhu, Linchao",
"Yang, Yi"
] | {F}rag{R}el: Exploiting Fragment-level Relations in the External Memory of Large Language Models | findings-acl.968 | Poster | 2406.03092v1 |
https://aclanthology.org/2024.findings-acl.969.bib | @inproceedings{meng-etal-2024-robustness,
title = "On the Robustness of Document-Level Relation Extraction Models to Entity Name Variations",
author = "Meng, Shiao and
Hu, Xuming and
Liu, Aiwei and
Ma, Fukun and
Yang, Yawen and
Li, Shuang and
Wen, Lijie",
editor = "... | Driven by the demand for cross-sentence and large-scale relation extraction, document-level relation extraction (DocRE) has attracted increasing research interest. Despite the continuous improvement in performance, we find that existing DocRE models which initially perform well may make more mistakes when merely changi... | [
"Meng, Shiao",
"Hu, Xuming",
"Liu, Aiwei",
"Ma, Fukun",
"Yang, Yawen",
"Li, Shuang",
"Wen, Lijie"
] | On the Robustness of Document-Level Relation Extraction Models to Entity Name Variations | findings-acl.969 | Poster | 2406.07444v1 |
https://aclanthology.org/2024.findings-acl.970.bib | @inproceedings{hu-etal-2024-resemo,
title = "{RESEMO}: A Benchmark {C}hinese Dataset for Studying Responsive Emotion from Social Media Content",
author = "Hu, Bo and
Zhang, Meng and
Xie, Chenfei and
Tian, Yuanhe and
Song, Yan and
Mao, Zhendong",
editor = "Ku, Lun-Wei and
... | On social media platforms, users{'} emotions are triggered when they encounter particular content from other users,where such emotions are different from those that spontaneously emerged, owing to the {``}responsive{''} nature. Analyzing the aforementioned responsive emotions from user interactions is a task of signifi... | [
"Hu, Bo",
"Zhang, Meng",
"Xie, Chenfei",
"Tian, Yuanhe",
"Song, Yan",
"Mao, Zhendong"
] | {RESEMO}: A Benchmark {C}hinese Dataset for Studying Responsive Emotion from Social Media Content | findings-acl.970 | Poster | 1506.06021v1 |
https://aclanthology.org/2024.findings-acl.971.bib | @inproceedings{ryu-etal-2024-ehr,
title = "{EHR}-{S}eq{SQL} : A Sequential Text-to-{SQL} Dataset For Interactively Exploring Electronic Health Records",
author = "Ryu, Jaehee and
Cho, Seonhee and
Lee, Gyubok and
Choi, Edward",
editor = "Ku, Lun-Wei and
Martins, Andre and
S... | In this paper, we introduce EHR-SeqSQL, a novel sequential text-to-SQL dataset for Electronic Health Record (EHR) databases. EHR-SeqSQL is designed to address critical yet underexplored aspects in text-to-SQL parsing: interactivity, compositionality, and efficiency. To the best of our knowledge, EHR-SeqSQL is not only ... | [
"Ryu, Jaehee",
"Cho, Seonhee",
"Lee, Gyubok",
"Choi, Edward"
] | {EHR}-{S}eq{SQL} : A Sequential Text-to-{SQL} Dataset For Interactively Exploring Electronic Health Records | findings-acl.971 | Poster | 2406.00019v3 |
https://aclanthology.org/2024.findings-acl.972.bib | @inproceedings{wang-etal-2024-keep,
title = "{KEEP} {CHATTING}! An Attractive Dataset for Continuous Conversation Agents",
author = "Wang, Yihe and
Liu, Jin and
Wan, Yao and
Li, Yitong and
Liu, Zifeng and
Chen, Weipeng",
editor = "Ku, Lun-Wei and
Martins, Andre and... | Ongoing chatting is an important step for conversational agents to build long-term connections with people. However, people tend to quickly lose interest in chatting if the conversational agent{'}s words are not engaging enough. In this paper, we present a novel task of increasing users{'} willingness to continue talki... | [
"Wang, Yihe",
"Liu, Jin",
"Wan, Yao",
"Li, Yitong",
"Liu, Zifeng",
"Chen, Weipeng"
] | {KEEP} {CHATTING}! An Attractive Dataset for Continuous Conversation Agents | findings-acl.972 | Poster | 2401.02978v1 |
https://aclanthology.org/2024.findings-acl.973.bib | @inproceedings{zhao-etal-2024-repair,
title = "{R}e{P}air: Automated Program Repair with Process-based Feedback",
author = "Zhao, Yuze and
Huang, Zhenya and
Ma, Yixiao and
Li, Rui and
Zhang, Kai and
Jiang, Hao and
Liu, Qi and
Zhu, Linbo and
Su, Yu",
ed... | The gap between the trepidation of program reliability and the expense of repairs underscore the indispensability for Automated Program Repair (APR). APR is instrumental in transforming vulnerable programs into more robust ones, bolstering program reliability while simultaneously diminishing the financial burden of man... | [
"Zhao, Yuze",
"Huang, Zhenya",
"Ma, Yixiao",
"Li, Rui",
"Zhang, Kai",
"Jiang, Hao",
"Liu, Qi",
"Zhu, Linbo",
"Su, Yu"
] | {R}e{P}air: Automated Program Repair with Process-based Feedback | findings-acl.973 | Poster | 2208.08235v1 |
https://aclanthology.org/2024.findings-acl.974.bib | @inproceedings{xu-etal-2024-concise,
title = "Concise and Precise Context Compression for Tool-Using Language Models",
author = "Xu, Yang and
Feng, Yunlong and
Mu, Honglin and
Hou, Yutai and
Li, Yitong and
Wang, Xinghao and
Zhong, Wanjun and
Li, Zhongyang and
... | Through reading the documentation in the context, tool-using language models can dynamically extend their capability using external tools. The cost is that we have to input lengthy documentation every time the model needs to use the tool, occupying the input window as well as slowing down the decoding process.Given the... | [
"Xu, Yang",
"Feng, Yunlong",
"Mu, Honglin",
"Hou, Yutai",
"Li, Yitong",
"Wang, Xinghao",
"Zhong, Wanjun",
"Li, Zhongyang",
"Tu, D",
"an",
"Zhu, Qingfu",
"Zhang, Min",
"Che, Wanxiang"
] | Concise and Precise Context Compression for Tool-Using Language Models | findings-acl.974 | Poster | 2407.02043v1 |
https://aclanthology.org/2024.findings-acl.975.bib | @inproceedings{elgaar-etal-2024-meddec,
title = "{M}ed{D}ec: A Dataset for Extracting Medical Decisions from Discharge Summaries",
author = "Elgaar, Mohamed and
Cheng, Jiali and
Vakil, Nidhi and
Amiri, Hadi and
Celi, Leo Anthony",
editor = "Ku, Lun-Wei and
Martins, Andre ... | Medical decisions directly impact individuals{'} health and well-being. Extracting decision spans from clinical notes plays a crucial role in understanding medical decision-making processes. In this paper, we develop a new dataset called {``}MedDec,{''} which contains clinical notes of eleven different phenotypes (dise... | [
"Elgaar, Mohamed",
"Cheng, Jiali",
"Vakil, Nidhi",
"Amiri, Hadi",
"Celi, Leo Anthony"
] | {M}ed{D}ec: A Dataset for Extracting Medical Decisions from Discharge Summaries | findings-acl.975 | Poster | 2305.15222v1 |
https://aclanthology.org/2024.alvr-1.1.bib | @inproceedings{schneider-biemann-2024-wismir3,
title = "{WISMIR}3: A Multi-Modal Dataset to Challenge Text-Image Retrieval Approaches",
author = "Schneider, Florian and
Biemann, Chris",
editor = "Gu, Jing and
Fu, Tsu-Jui (Ray) and
Hudson, Drew and
Celikyilmaz, Asli and
Wan... | This paper presents WISMIR3, a multi-modal dataset comprising roughly 300K text-image pairs from Wikipedia. With a sophisticated automatic ETL pipeline, we scraped, filtered, and transformed the data so that WISMIR3 intrinsically differs from other popular text-image datasets like COCO and Flickr30k. We prove this diff... | [
"Schneider, Florian",
"Biemann, Chris"
] | {WISMIR}3: A Multi-Modal Dataset to Challenge Text-Image Retrieval Approaches | alvr-1.1 | Poster | 1712.09550v2 |
https://aclanthology.org/2024.alvr-1.2.bib | @inproceedings{geigle-etal-2024-mblip,
title = "m{BLIP}: Efficient Bootstrapping of Multilingual Vision-{LLM}s",
author = "Geigle, Gregor and
Jain, Abhay and
Timofte, Radu and
Glava{\v{s}}, Goran",
editor = "Gu, Jing and
Fu, Tsu-Jui (Ray) and
Hudson, Drew and
Celiky... | Modular vision-language models (Vision-LLMs) align pretrained image encoders with (frozen) large language models (LLMs) and post-hoc condition LLMs to {`}understand{'} the image input. With the abundance of readily available high-quality English image-text data as well as strong monolingual English LLMs, the research f... | [
"Geigle, Gregor",
"Jain, Abhay",
"Timofte, Radu",
"Glava{\\v{s}}, Goran"
] | m{BLIP}: Efficient Bootstrapping of Multilingual Vision-{LLM}s | alvr-1.2 | Poster | 2106.03469v2 |
https://aclanthology.org/2024.alvr-1.3.bib | @inproceedings{xia-etal-2024-lmpt,
title = "{LMPT}: Prompt Tuning with Class-Specific Embedding Loss for Long-Tailed Multi-Label Visual Recognition",
author = "Xia, Peng and
Xu, Di and
Hu, Ming and
Ju, Lie and
Ge, Zongyuan",
editor = "Gu, Jing and
Fu, Tsu-Jui (Ray) and
... | Long-tailed multi-label visual recognition (LTML) task is a highly challenging task due to the label co-occurrence and imbalanced data distribution. In this work, we propose a unified framework for LTML, namely prompt tuning with class-specific embedding loss (LMPT), capturing the semantic feature interactions between ... | [
"Xia, Peng",
"Xu, Di",
"Hu, Ming",
"Ju, Lie",
"Ge, Zongyuan"
] | {LMPT}: Prompt Tuning with Class-Specific Embedding Loss for Long-Tailed Multi-Label Visual Recognition | alvr-1.3 | Poster | 2305.04536v2 |
https://aclanthology.org/2024.alvr-1.4.bib | @inproceedings{lovenia-etal-2024-negative,
title = "Negative Object Presence Evaluation ({NOPE}) to Measure Object Hallucination in Vision-Language Models",
author = "Lovenia, Holy and
Dai, Wenliang and
Cahyawijaya, Samuel and
Ji, Ziwei and
Fung, Pascale",
editor = "Gu, Jing and... | Object hallucination poses a significant challenge in vision-language (VL) models, often leading to the generation of nonsensical or unfaithful responses with non-existent objects. However, the absence of a general measurement for evaluating object hallucination in VL models has hindered our understanding and ability t... | [
"Lovenia, Holy",
"Dai, Wenliang",
"Cahyawijaya, Samuel",
"Ji, Ziwei",
"Fung, Pascale"
] | Negative Object Presence Evaluation ({NOPE}) to Measure Object Hallucination in Vision-Language Models | alvr-1.4 | Poster | 2310.05338v2 |
https://aclanthology.org/2024.alvr-1.5.bib | @inproceedings{quantmeyer-etal-2024-clip,
title = "How and where does {CLIP} process negation?",
author = "Quantmeyer, Vincent and
Mosteiro, Pablo and
Gatt, Albert",
editor = "Gu, Jing and
Fu, Tsu-Jui (Ray) and
Hudson, Drew and
Celikyilmaz, Asli and
Wang, William",
... | Various benchmarks have been proposed to test linguistic understanding in pre-trained vision {\&} language (VL) models. Here we build on the existence task from the VALSE benchmark (Parcalabescu et al., 2022) which we use to test models{'} understanding of negation, a particularly interesting issue for multimodal model... | [
"Quantmeyer, Vincent",
"Mosteiro, Pablo",
"Gatt, Albert"
] | How and where does {CLIP} process negation? | alvr-1.5 | Poster | 2407.10488v1 |
https://aclanthology.org/2024.alvr-1.6.bib | @inproceedings{nikandrou-etal-2024-enhancing,
title = "Enhancing Continual Learning in Visual Question Answering with Modality-Aware Feature Distillation",
author = "Nikandrou, Malvina and
Pantazopoulos, Georgios and
Konstas, Ioannis and
Suglia, Alessandro",
editor = "Gu, Jing and
... | Continual learning focuses on incrementally training a model on a sequence of tasks with the aim of learning new tasks while minimizing performance drop on previous tasks. Existing approaches at the intersection of Continual Learning and Visual Question Answering (VQA) do not study how the multimodal nature of the inpu... | [
"Nik",
"rou, Malvina",
"Pantazopoulos, Georgios",
"Konstas, Ioannis",
"Suglia, Aless",
"ro"
] | Enhancing Continual Learning in Visual Question Answering with Modality-Aware Feature Distillation | alvr-1.6 | Poster | 2406.19297v1 |
https://aclanthology.org/2024.alvr-1.7.bib | @inproceedings{teramen-etal-2024-english,
title = "{E}nglish-to-{J}apanese Multimodal Machine Translation Based on Image-Text Matching of Lecture Videos",
author = "Teramen, Ayu and
Ohtsuka, Takumi and
Kondo, Risa and
Kajiwara, Tomoyuki and
Ninomiya, Takashi",
editor = "Gu, Jing ... | We work on a multimodal machine translation of the audio contained in English lecture videos to generate Japanese subtitles. Image-guided multimodal machine translation is promising for error correction in speech recognition and for text disambiguation. In our situation, lecture videos provide a variety of images. Imag... | [
"Teramen, Ayu",
"Ohtsuka, Takumi",
"Kondo, Risa",
"Kajiwara, Tomoyuki",
"Ninomiya, Takashi"
] | {E}nglish-to-{J}apanese Multimodal Machine Translation Based on Image-Text Matching of Lecture Videos | alvr-1.7 | Poster | 2006.12799v1 |
https://aclanthology.org/2024.alvr-1.8.bib | @inproceedings{wang-etal-2024-videocot,
title = "{V}ideo{C}o{T}: A Video Chain-of-Thought Dataset with Active Annotation Tool",
author = "Wang, Yan and
Zeng, Yawen and
Zheng, Jingsheng and
Xing, Xiaofen and
Xu, Jin and
Xu, Xiangmin",
editor = "Gu, Jing and
Fu, Tsu-J... | Multimodal large language models (MLLMs) are flourishing, but mainly focus on images with less attention than videos, especially in sub-fields such as prompt engineering, video chain-of-though (CoT), and instruction tuning on videos. Therefore, we try to explore the collection of CoT datasets in videos to lead to video... | [
"Wang, Yan",
"Zeng, Yawen",
"Zheng, Jingsheng",
"Xing, Xiaofen",
"Xu, Jin",
"Xu, Xiangmin"
] | {V}ideo{C}o{T}: A Video Chain-of-Thought Dataset with Active Annotation Tool | alvr-1.8 | Poster | 2407.05355v1 |
https://aclanthology.org/2024.alvr-1.9.bib | @inproceedings{rosch-etal-2024-enhancing,
title = "Enhancing Conceptual Understanding in Multimodal Contrastive Learning through Hard Negative Samples",
author = {R{\"o}sch, Philipp J. and
Oswald, Norbert and
Geierhos, Michaela and
Libovick{\'y}, Jind{\v{r}}ich},
editor = "Gu, Jing and... | Current vision-language models leveraging contrastive learning often face limitations in developing fine-grained conceptual understanding. This is due to random negative samples during pretraining, causing almost exclusively very dissimilar concepts to be compared in the loss function. Consequently, the models struggle... | [
"R{\\\"o}sch, Philipp J.",
"Oswald, Norbert",
"Geierhos, Michaela",
"Libovick{\\'y}, Jind{\\v{r}}ich"
] | Enhancing Conceptual Understanding in Multimodal Contrastive Learning through Hard Negative Samples | alvr-1.9 | Poster | 2403.02875v2 |
https://aclanthology.org/2024.alvr-1.10.bib | @inproceedings{xia-etal-2024-vision,
title = "Vision Language Models for Spreadsheet Understanding: Challenges and Opportunities",
author = "Xia, Shiyu and
Xiong, Junyu and
Dong, Haoyu and
Zhao, Jianbo and
Tian, Yuzhang and
Zhou, Mengyu and
He, Yeye and
Han, Shi ... | This paper explores capabilities of Vision Language Models on spreadsheet comprehension. We propose three self-supervised challenges with corresponding evaluation metrics to comprehensively evaluate VLMs on Optical Character Recognition (OCR), spatial perception, and visual format recognition. Additionally, we utilize ... | [
"Xia, Shiyu",
"Xiong, Junyu",
"Dong, Haoyu",
"Zhao, Jianbo",
"Tian, Yuzhang",
"Zhou, Mengyu",
"He, Yeye",
"Han, Shi",
"Zhang, Dongmei"
] | Vision Language Models for Spreadsheet Understanding: Challenges and Opportunities | alvr-1.10 | Poster | 2405.16234v2 |
https://aclanthology.org/2024.alvr-1.11.bib | @inproceedings{wang-etal-2024-slideavsr,
title = "{S}lide{AVSR}: A Dataset of Paper Explanation Videos for Audio-Visual Speech Recognition",
author = "Wang, Hao and
Kurita, Shuhei and
Shimizu, Shuichiro and
Kawahara, Daisuke",
editor = "Gu, Jing and
Fu, Tsu-Jui (Ray) and
H... | Audio-visual speech recognition (AVSR) is a multimodal extension of automatic speech recognition (ASR), using video as a complement to audio. In AVSR, considerable efforts have been directed at datasets for facial features such as lip-readings, while they often fall short in evaluating the image comprehension capabilit... | [
"Wang, Hao",
"Kurita, Shuhei",
"Shimizu, Shuichiro",
"Kawahara, Daisuke"
] | {S}lide{AVSR}: A Dataset of Paper Explanation Videos for Audio-Visual Speech Recognition | alvr-1.11 | Poster | 2401.09759v2 |
https://aclanthology.org/2024.alvr-1.12.bib | @inproceedings{hu-keller-2024-causal,
title = "Causal and Temporal Inference in Visual Question Generation by Utilizing Pre-trained Models",
author = "Hu, Zhanghao and
Keller, Frank",
editor = "Gu, Jing and
Fu, Tsu-Jui (Ray) and
Hudson, Drew and
Celikyilmaz, Asli and
Wang,... | Visual Question Generation is a task at the crossroads of visual and language learning, impacting broad domains like education, medicine, and social media. While existing pre-trained models excel in fact-based queries with image pairs, they fall short of capturing human-like inference, particularly in understanding cau... | [
"Hu, Zhanghao",
"Keller, Frank"
] | Causal and Temporal Inference in Visual Question Generation by Utilizing Pre-trained Models | alvr-1.12 | Poster | 2304.08083v2 |
https://aclanthology.org/2024.alvr-1.13.bib | @inproceedings{reinhardt-etal-2024-improving,
title = "Improving Vision-Language Cross-Lingual Transfer with Scheduled Unfreezing",
author = "Reinhardt, Max and
Geigle, Gregor and
Timofte, Radu and
Glava{\v{s}}, Goran",
editor = "Gu, Jing and
Fu, Tsu-Jui (Ray) and
Hudson, ... | Large-scale pretraining of vision-language (VL) models brought dramatic improvements across numerous tasks, from visual question-answering to cross-modal retrieval but these gains are mostly limited to English. Massively multilingual VL encoder models (mVLMs) hold promise for other languages: after fine-tuning on only ... | [
"Reinhardt, Max",
"Geigle, Gregor",
"Timofte, Radu",
"Glava{\\v{s}}, Goran"
] | Improving Vision-Language Cross-Lingual Transfer with Scheduled Unfreezing | alvr-1.13 | Poster | 2301.05487v2 |
https://aclanthology.org/2024.alvr-1.14.bib | @inproceedings{zhu-etal-2024-automatic,
title = "Automatic Layout Planning for Visually-Rich Documents with Instruction-Following Models",
author = "Zhu, Wanrong and
Zhang, Ruiyi and
Healey, Jennifer and
Wang, William Yang and
Sun, Tong",
editor = "Gu, Jing and
Fu, Tsu-Jui... | Recent advancements in instruction-following models have made user interactions with models more user-friendly and efficient, broadening their applicability. In graphic design, non-professional users often struggle to create visually appealing layouts due to limited skills and resources. In this work, we introduce a no... | [
"Zhu, Wanrong",
"Zhang, Ruiyi",
"Healey, Jennifer",
"Wang, William Yang",
"Sun, Tong"
] | Automatic Layout Planning for Visually-Rich Documents with Instruction-Following Models | alvr-1.14 | Poster | 2404.15271v1 |
https://aclanthology.org/2024.alvr-1.15.bib | @inproceedings{urailertprasert-etal-2024-sea,
title = "{SEA}-{VQA}: {S}outheast {A}sian Cultural Context Dataset For Visual Question Answering",
author = "Urailertprasert, Norawit and
Limkonchotiwat, Peerat and
Suwajanakorn, Supasorn and
Nutanong, Sarana",
editor = "Gu, Jing and
... | Visual Question Answering (VQA) is a critical task that requires the simultaneous understanding of visual and textual information. While significant advancements have been made with multilingual datasets, these often lack cultural specificity, especially in the context of Southeast Asia (SEA). In this paper, we introdu... | [
"Urailertprasert, Norawit",
"Limkonchotiwat, Peerat",
"Suwajanakorn, Supasorn",
"Nutanong, Sarana"
] | {SEA}-{VQA}: {S}outheast {A}sian Cultural Context Dataset For Visual Question Answering | alvr-1.15 | Poster | 2402.05374v2 |
https://aclanthology.org/2024.alvr-1.16.bib | @inproceedings{bielefeld-etal-2024-wiki,
title = "{W}iki-{VEL}: Visual Entity Linking for Structured Data on Wikimedia Commons",
author = {Bielefeld, Philipp and
Geppert, Jasmin and
G{\"u}ven, Necdet and
John, Melna and
Ziupka, Adrian and
Kaffee, Lucie-Aim{\'e}e and
Bis... | Describing Wikimedia Commons images using Wikidata{'}s structured data enables a wide range of automation tasks, such as search and organization, as well as downstream tasks, such as labeling images or training machine learning models. However, there is currently a lack of structured data-labelled images on Wikimedia C... | [
"Bielefeld, Philipp",
"Geppert, Jasmin",
"G{\\\"u}ven, Necdet",
"John, Melna",
"Ziupka, Adrian",
"Kaffee, Lucie-Aim{\\'e}e",
"Biswas, Russa",
"De Melo, Gerard"
] | {W}iki-{VEL}: Visual Entity Linking for Structured Data on Wikimedia Commons | alvr-1.16 | Poster | 1507.04180v1 |
https://aclanthology.org/2024.alvr-1.17.bib | @inproceedings{wazni-etal-2024-verbclip,
title = "{V}erb{CLIP}: Improving Verb Understanding in Vision-Language Models with Compositional Structures",
author = "Wazni, Hadi and
Lo, Kin and
Sadrzadeh, Mehrnoosh",
editor = "Gu, Jing and
Fu, Tsu-Jui (Ray) and
Hudson, Drew and
... | Verbs describe the dynamics of interactions between people, objects, and their environments. They play a crucial role in language formation and understanding. Nonetheless, recent vision-language models like CLIP predominantly rely on nouns and have a limited account of verbs. This limitation affects their performance i... | [
"Wazni, Hadi",
"Lo, Kin",
"Sadrzadeh, Mehrnoosh"
] | {V}erb{CLIP}: Improving Verb Understanding in Vision-Language Models with Compositional Structures | alvr-1.17 | Poster | 2304.06708v1 |
https://aclanthology.org/2024.alvr-1.18.bib | @inproceedings{narin-2024-evolutionary,
title = "Evolutionary Reward Design and Optimization with Multimodal Large Language Models",
author = "Narin, Ali",
editor = "Gu, Jing and
Fu, Tsu-Jui (Ray) and
Hudson, Drew and
Celikyilmaz, Asli and
Wang, William",
booktitle = "Proceed... | Designing reward functions is a pivotal yet challenging task for Reinforcement Learning (RL) practices, often demanding domain expertise and substantial effort. Recent studies have explored the utilization of Large Language Models (LLMs) to generate reward functions via evolutionary search techniques. However, these ap... | [
"Narin, Ali"
] | Evolutionary Reward Design and Optimization with Multimodal Large Language Models | alvr-1.18 | Poster | 2406.10540v1 |
https://aclanthology.org/2024.arabicnlp-1.1.bib | @inproceedings{abdaljalil-mubarak-2024-wikidata,
title = "{W}ikidata as a Source of Demographic Information",
author = "Abdaljalil, Samir and
Mubarak, Hamdy",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Nadi and
Abu Farha, Ibrahim and
Ab... | Names carry important information about our identities and demographics such as gender, nationality, ethnicity, etc. We investigate the use of individual{'}s name, in both Arabic and English, to predict important attributes, namely country, region, gender, and language. We extract data from Wikidata, and normalize it, ... | [
"Abdaljalil, Samir",
"Mubarak, Hamdy"
] | {W}ikidata as a Source of Demographic Information | arabicnlp-1.1 | Poster | 1908.11153v2 |
https://aclanthology.org/2024.arabicnlp-1.2.bib | @inproceedings{almutairi-etal-2024-synthetic,
title = "Synthetic {A}rabic Medical Dialogues Using Advanced Multi-Agent {LLM} Techniques",
author = "ALMutairi, Mariam and
AlKulaib, Lulwah and
Aktas, Melike and
Alsalamah, Sara and
Lu, Chang-Tien",
editor = "Habash, Nizar and
... | The increasing use of artificial intelligence in healthcare requires robust datasets for training and validation, particularly in the domain of medical conversations. However, the creation and accessibility of such datasets in Arabic face significant challenges, especially due to the sensitivity and privacy concerns th... | [
"ALMutairi, Mariam",
"AlKulaib, Lulwah",
"Aktas, Melike",
"Alsalamah, Sara",
"Lu, Chang-Tien"
] | Synthetic {A}rabic Medical Dialogues Using Advanced Multi-Agent {LLM} Techniques | arabicnlp-1.2 | Poster | 2403.06611v1 |
https://aclanthology.org/2024.arabicnlp-1.3.bib | @inproceedings{haouari-etal-2024-aured,
title = "{A}u{RED}: Enabling {A}rabic Rumor Verification using Evidence from Authorities over {T}witter",
author = "Haouari, Fatima and
Elsayed, Tamer and
Suwaileh, Reem",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
... | Diverging from the trend of the previous rumor verification studies, we introduce the new task of rumor verification using evidence that are exclusively captured from authorities, i.e., entities holding the right and knowledge to verify corresponding information. To enable research on this task for Arabic low-resourced... | [
"Haouari, Fatima",
"Elsayed, Tamer",
"Suwaileh, Reem"
] | {A}u{RED}: Enabling {A}rabic Rumor Verification using Evidence from Authorities over {T}witter | arabicnlp-1.3 | Poster | 2301.05863v1 |
https://aclanthology.org/2024.arabicnlp-1.4.bib | @inproceedings{alhafni-etal-2024-exploiting,
title = "Exploiting Dialect Identification in Automatic Dialectal Text Normalization",
author = "Alhafni, Bashar and
Al-Towaity, Sarah and
Fawzy, Ziyad and
Nassar, Fatema and
Eryani, Fadhl and
Bouamor, Houda and
Habash, Nizar... | Dialectal Arabic is the primary spoken language used by native Arabic speakers in daily communication. The rise of social media platforms has notably expanded its use as a written language. However, Arabic dialects do not have standard orthographies. This, combined with the inherent noise in user-generated content on s... | [
"Alhafni, Bashar",
"Al-Towaity, Sarah",
"Fawzy, Ziyad",
"Nassar, Fatema",
"Eryani, Fadhl",
"Bouamor, Houda",
"Habash, Nizar"
] | Exploiting Dialect Identification in Automatic Dialectal Text Normalization | arabicnlp-1.4 | Poster | 2407.03020v1 |
https://aclanthology.org/2024.arabicnlp-1.5.bib | @inproceedings{liberato-etal-2024-strategies,
title = "Strategies for {A}rabic Readability Modeling",
author = "Liberato, Juan and
Alhafni, Bashar and
Khalil, Muhamed and
Habash, Nizar",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Nadi ... | Automatic readability assessment is relevant to building NLP applications for education, content analysis, and accessibility. However, Arabic readability assessment is a challenging task due to Arabic{'}s morphological richness and limited readability resources. In this paper, we present a set of experimental results o... | [
"Liberato, Juan",
"Alhafni, Bashar",
"Khalil, Muhamed",
"Habash, Nizar"
] | Strategies for {A}rabic Readability Modeling | arabicnlp-1.5 | Poster | 2407.03032v1 |
https://aclanthology.org/2024.arabicnlp-1.6.bib | @inproceedings{mraikhat-etal-2024-areej,
title = "{AREE}j: {A}rabic Relation Extraction with Evidence",
author = "Mraikhat, Osama and
Hamoud, Hadi and
Zaraket, Fadi",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Nadi and
Abu Farha, Ibrahi... | Relational entity extraction is key in building knowledge graphs. A relational entity has a source, a tail and atype. In this paper, we consider Arabic text and introduce evidence enrichment which intuitivelyinforms models for better predictions. Relational evidence is an expression in the textthat explains how sources... | [
"Mraikhat, Osama",
"Hamoud, Hadi",
"Zaraket, Fadi"
] | {AREE}j: {A}rabic Relation Extraction with Evidence | arabicnlp-1.6 | Poster | 2106.08657v2 |
https://aclanthology.org/2024.arabicnlp-1.7.bib | @inproceedings{boughorbel-etal-2024-improving,
title = "Improving Language Models Trained on Translated Data with Continual Pre-Training and Dictionary Learning Analysis",
author = "Boughorbel, Sabri and
Parvez, Md Rizwan and
Hawasly, Majd",
editor = "Habash, Nizar and
Bouamor, Houda a... | Training LLMs in low resources languages usually utilizes machine translation (MT) data augmentation from English language. However, translation brings a number of challenges: there are large costs attached to translating and curating huge amounts of content with high-end machine translation solutions; the translated c... | [
"Boughorbel, Sabri",
"Parvez, Md Rizwan",
"Hawasly, Majd"
] | Improving Language Models Trained on Translated Data with Continual Pre-Training and Dictionary Learning Analysis | arabicnlp-1.7 | Poster | 2405.14277v2 |
https://aclanthology.org/2024.arabicnlp-1.8.bib | @inproceedings{elnokrashy-alkhamissi-2024-context,
title = "A Context-Contrastive Inference Approach To Partial Diacritization",
author = "ElNokrashy, Muhammad and
AlKhamissi, Badr",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Nadi and
Abu Farh... | Diacritization plays a pivotal role for meaning disambiguation and improving readability in Arabic texts. Efforts have long focused on marking every eligible character (Full Diacritization). Overlooked in comparison, Partial Diacritzation ({`}PD{`}) is the selection of a subset of characters to be annotated to aid comp... | [
"ElNokrashy, Muhammad",
"AlKhamissi, Badr"
] | A Context-Contrastive Inference Approach To Partial Diacritization | arabicnlp-1.8 | Poster | 2401.08919v3 |
https://aclanthology.org/2024.arabicnlp-1.9.bib | @inproceedings{al-barham-etal-2024-araclip,
title = "{A}ra{CLIP}: Cross-Lingual Learning for Effective {A}rabic Image Retrieval",
author = "Al-Barham, Muhammad and
Afyouni, Imad and
Almubarak, Khalid and
Elnagar, Ashraf and
Turky, Ayad and
Hashem, Ibrahim",
editor = "Habas... | This paper introduces Arabic Contrastive Language-Image Pre-training (AraCLIP), a model designed for Arabic image retrieval tasks, building upon the Contrastive Language-Image Pre-training (CLIP) architecture. AraCLIP leverages Knowledge Distillation to transfer cross-modal knowledge from English to Arabic, enhancing i... | [
"Al-Barham, Muhammad",
"Afyouni, Imad",
"Almubarak, Khalid",
"Elnagar, Ashraf",
"Turky, Ayad",
"Hashem, Ibrahim"
] | {A}ra{CLIP}: Cross-Lingual Learning for Effective {A}rabic Image Retrieval | arabicnlp-1.9 | Poster | 2006.11586v1 |
https://aclanthology.org/2024.arabicnlp-1.10.bib | @inproceedings{elfqih-monti-2024-large,
title = "Large Language Models as Legal Translators of {A}rabic Legislatives: Does {C}hat{GPT} and Gemini Care for Context and Terminology?",
author = "ElFqih, Khadija and
Monti, Johanna",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, R... | Accurate translation of terminology and adaptation to in-context information is a pillar to high quality translation. Recently, there is a remarkable interest towards the use and the evaluation of Large Language Models (LLMs) particularly for Machine Translation tasks. Nevertheless, despite their recent advancement and... | [
"ElFqih, Khadija",
"Monti, Johanna"
] | Large Language Models as Legal Translators of {A}rabic Legislatives: Does {C}hat{GPT} and Gemini Care for Context and Terminology? | arabicnlp-1.10 | Poster | 2308.03051v2 |
https://aclanthology.org/2024.arabicnlp-1.11.bib | @inproceedings{doan-etal-2024-towards,
title = "Towards Zero-Shot Text-To-Speech for {A}rabic Dialects",
author = "Doan, Khai and
Waheed, Abdul and
Abdul-Mageed, Muhammad",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Nadi and
Abu Farha, ... | Zero-shot multi-speaker text-to-speech (ZS-TTS) systems have advanced for English, however, it still lags behind due to insufficient resources. We address this gap for Arabic, a language of more than 450 million native speakers, by first adapting a sizeable existing dataset to suit the needs of speech synthesis. Additi... | [
"Doan, Khai",
"Waheed, Abdul",
"Abdul-Mageed, Muhammad"
] | Towards Zero-Shot Text-To-Speech for {A}rabic Dialects | arabicnlp-1.11 | Poster | 2105.14779v2 |
https://aclanthology.org/2024.arabicnlp-1.12.bib | @inproceedings{mdhaffar-etal-2024-performance,
title = "Performance Analysis of Speech Encoders for Low-Resource {SLU} and {ASR} in {T}unisian Dialect",
author = "Mdhaffar, Salima and
Elleuch, Haroun and
Bougares, Fethi and
Est{\`e}ve, Yannick",
editor = "Habash, Nizar and
Bouamo... | Speech encoders pretrained through self-supervised learning (SSL) have demonstrated remarkable performance in various downstream tasks, including Spoken Language Understanding (SLU) and Automatic Speech Recognition (ASR). For instance, fine-tuning SSL models for such tasks has shown significant potential, leading to im... | [
"Mdhaffar, Salima",
"Elleuch, Haroun",
"Bougares, Fethi",
"Est{\\`e}ve, Yannick"
] | Performance Analysis of Speech Encoders for Low-Resource {SLU} and {ASR} in {T}unisian Dialect | arabicnlp-1.12 | Poster | 2407.04533v2 |
https://aclanthology.org/2024.arabicnlp-1.13.bib | @inproceedings{el-shangiti-etal-2024-arabic,
title = "{A}rabic Automatic Story Generation with Large Language Models",
author = "El-Shangiti, Ahmed and
Alwajih, Fakhraddin and
Abdul-Mageed, Muhammad",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh,... | Large language models (LLMs) have recently emerged as a powerful tool for a wide range of language generation tasks. Nevertheless, this progress has been slower in Arabic. In this work, we focus on the task of generating stories from LLMs. For our training, we use stories acquired through machine translation (MT) as we... | [
"El-Shangiti, Ahmed",
"Alwajih, Fakhraddin",
"Abdul-Mageed, Muhammad"
] | {A}rabic Automatic Story Generation with Large Language Models | arabicnlp-1.13 | Poster | 2407.07551v1 |
https://aclanthology.org/2024.arabicnlp-1.14.bib | @inproceedings{ahmed-etal-2024-alclam,
title = "{A}lcla{M}: {A}rabic Dialect Language Model",
author = "Ahmed, Murtadha and
Alfasly, Saghir and
Wen, Bo and
Addeen, Jamal and
Ahmed, Mohammed and
Liu, Yunfeng",
editor = "Habash, Nizar and
Bouamor, Houda and
Esk... | Pre-trained Language Models (PLMs) are integral to many modern natural language processing (NLP) systems. Although multilingual models cover a wide range of languages, they often grapple with challenges like high inference costs and a lack of diverse non-English training data. Arabic-specific PLMs are trained predomina... | [
"Ahmed, Murtadha",
"Alfasly, Saghir",
"Wen, Bo",
"Addeen, Jamal",
"Ahmed, Mohammed",
"Liu, Yunfeng"
] | {A}lcla{M}: {A}rabic Dialect Language Model | arabicnlp-1.14 | Poster | 2305.16651v1 |
https://aclanthology.org/2024.arabicnlp-1.15.bib | @inproceedings{shatnawi-etal-2024-data,
title = "Data Augmentation for Speech-Based Diacritic Restoration",
author = "Shatnawi, Sara and
Alqahtani, Sawsan and
Shehata, Shady and
Aldarmaki, Hanan",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tom... | This paper describes a data augmentation technique for boosting the performance of speech-based diacritic restoration. Our experiments demonstrate the utility of this appraoch, resulting in improved generalization of all models across different test sets. In addition, we describe the first multi-modal diacritic restora... | [
"Shatnawi, Sara",
"Alqahtani, Sawsan",
"Shehata, Shady",
"Aldarmaki, Hanan"
] | Data Augmentation for Speech-Based Diacritic Restoration | arabicnlp-1.15 | Poster | 2311.10771v2 |
https://aclanthology.org/2024.arabicnlp-1.16.bib | @inproceedings{mokh-etal-2024-domain,
title = "Out-of-Domain Dependency Parsing for Dialects of {A}rabic: A Case Study",
author = {Mokh, Noor and
Dakota, Daniel and
K{\"u}bler, Sandra},
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Nadi and
... | We study dependency parsing for four Arabic dialects (Gulf, Levantine, Egyptian, and Maghrebi). Since no syntactically annotated data exist for Arabic dialects, we train the parser on a Modern Standard Arabic (MSA) corpus, which creates an out-of-domain setting.We investigate methods to close the gap between the source... | [
"Mokh, Noor",
"Dakota, Daniel",
"K{\\\"u}bler, S",
"ra"
] | Out-of-Domain Dependency Parsing for Dialects of {A}rabic: A Case Study | arabicnlp-1.16 | Poster | 2005.00318v1 |
https://aclanthology.org/2024.arabicnlp-1.17.bib | @inproceedings{bassas-kubler-2024-investigating,
title = "Investigating Linguistic Features for {A}rabic {NLI}",
author = {Bassas, Yasmeen and
K{\"u}bler, Sandra},
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Nadi and
Abu Farha, Ibrahim and
... | Native Language Identification (NLI) is concerned with predicting the native language of an author writing in a second language. We investigate NLI for Arabic, with a focus on the types of linguistic information given that Arabic is morphologically rich. We use the Arabic Learner Corpus (ALC) foro training and testing ... | [
"Bassas, Yasmeen",
"K{\\\"u}bler, S",
"ra"
] | Investigating Linguistic Features for {A}rabic {NLI} | arabicnlp-1.17 | Poster | 2309.06923v1 |
https://aclanthology.org/2024.arabicnlp-1.18.bib | @inproceedings{demidova-etal-2024-john,
title = "John vs. Ahmed: Debate-Induced Bias in Multilingual {LLM}s",
author = "Demidova, Anastasiia and
Atwany, Hanin and
Rabih, Nour and
Sha{'}ban, Sanad and
Abdul-Mageed, Muhammad",
editor = "Habash, Nizar and
Bouamor, Houda and
... | Large language models (LLMs) play a crucial role in a wide range of real world applications. However, concerns about their safety and ethical implications are growing. While research on LLM safety is expanding, there is a noticeable gap in evaluating safety across multiple languages, especially in Arabic and Russian. W... | [
"Demidova, Anastasiia",
"Atwany, Hanin",
"Rabih, Nour",
"Sha{'}ban, Sanad",
"Abdul-Mageed, Muhammad"
] | John vs. Ahmed: Debate-Induced Bias in Multilingual {LLM}s | arabicnlp-1.18 | Poster | 2402.18045v2 |
https://aclanthology.org/2024.arabicnlp-1.19.bib | @inproceedings{bhatia-etal-2024-qalam,
title = "Qalam: A Multimodal {LLM} for {A}rabic Optical Character and Handwriting Recognition",
author = "Bhatia, Gagan and
Nagoudi, El Moatez Billah and
Alwajih, Fakhraddin and
Abdul-Mageed, Muhammad",
editor = "Habash, Nizar and
Bouamor, H... | Arabic Optical Character Recognition (OCR) and Handwriting Recognition (HWR) pose unique challenges due to the cursive and context-sensitive nature of the Arabic script. This study introduces ***Qalam***, a novel foundation model designed for Arabic OCR and HWR, built on a SwinV2 encoder and RoBERTa decoder architectur... | [
"Bhatia, Gagan",
"Nagoudi, El Moatez Billah",
"Alwajih, Fakhraddin",
"Abdul-Mageed, Muhammad"
] | Qalam: A Multimodal {LLM} for {A}rabic Optical Character and Handwriting Recognition | arabicnlp-1.19 | Poster | 2407.13559v1 |
https://aclanthology.org/2024.arabicnlp-1.20.bib | @inproceedings{hijazi-etal-2024-arablegaleval,
title = "{A}rab{L}egal{E}val: A Multitask Benchmark for Assessing {A}rabic Legal Knowledge in Large Language Models",
author = "Hijazi, Faris and
Alharbi, Somayah and
AlHussein, Abdulaziz and
Shairah, Harethah and
Alzahrani, Reem and
... | The rapid advancements in Large Language Models (LLMs) have led to significant improvements in various natural language processing tasks. However, the evaluation of LLMs{'} legal knowledge, particularly in non English languages such as Arabic, remains under-explored. To address this gap, we introduce ArabLegalEval, a m... | [
"Hijazi, Faris",
"Alharbi, Somayah",
"AlHussein, Abdulaziz",
"Shairah, Harethah",
"Alzahrani, Reem",
"Alshamlan, Hebah",
"Turkiyyah, George",
"Knio, Omar"
] | {A}rab{L}egal{E}val: A Multitask Benchmark for Assessing {A}rabic Legal Knowledge in Large Language Models | arabicnlp-1.20 | Poster | 2402.12840v2 |
https://aclanthology.org/2024.arabicnlp-1.21.bib | @inproceedings{alasmary-etal-2024-catt,
title = "{CATT}: Character-based {A}rabic Tashkeel Transformer",
author = "Alasmary, Faris and
Zaafarani, Orjuwan and
Ghannam, Ahmad",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Nadi and
Abu Farha... | Tashkeel, or Arabic Text Diacritization (ATD), greatly enhances the comprehension of Arabic text by removing ambiguity and minimizing the risk of misinterpretations caused by its absence.It plays a crucial role in improving Arabic text processing, particularly in applications such as text-to-speech and machine translat... | [
"Alasmary, Faris",
"Zaafarani, Orjuwan",
"Ghannam, Ahmad"
] | {CATT}: Character-based {A}rabic Tashkeel Transformer | arabicnlp-1.21 | Poster | 2407.03236v3 |
https://aclanthology.org/2024.arabicnlp-1.22.bib | @inproceedings{khalifa-etal-2024-picking,
title = "Picking Up Where the Linguist Left Off: Mapping Morphology to Phonology through Learning the Residuals",
author = "Khalifa, Salam and
Qaddoumi, Abdelrahim and
Broselow, Ellen and
Rambow, Owen",
editor = "Habash, Nizar and
Bouamor... | Learning morphophonological mappings between the spoken form of a language and its underlying morphological structures is crucial for enriching resources for morphologically rich languages like Arabic. In this work, we focus on Egyptian Arabic as our case study and explore the integration of linguistic knowledge with a... | [
"Khalifa, Salam",
"Qaddoumi, Abdelrahim",
"Broselow, Ellen",
"Rambow, Owen"
] | Picking Up Where the Linguist Left Off: Mapping Morphology to Phonology through Learning the Residuals | arabicnlp-1.22 | Poster | 9607013v1 |
https://aclanthology.org/2024.arabicnlp-1.23.bib | @inproceedings{alcoba-inciarte-etal-2024-utility,
title = "On the Utility of Pretraining Language Models on Synthetic Data",
author = "Alcoba Inciarte, Alcides and
Kwon, Sang Yun and
Nagoudi, El Moatez Billah and
Abdul-Mageed, Muhammad",
editor = "Habash, Nizar and
Bouamor, Houda... | Development of pre-trained language models has predominantly relied on large amounts of datasets. However, this dependence on abundant data has limited the applicability of these models in low-resource settings. In this work, we investigate the utility of exploiting synthetic datasets acquired from different sources to... | [
"Alcoba Inciarte, Alcides",
"Kwon, Sang Yun",
"Nagoudi, El Moatez Billah",
"Abdul-Mageed, Muhammad"
] | On the Utility of Pretraining Language Models on Synthetic Data | arabicnlp-1.23 | Poster | 2403.13638v2 |
https://aclanthology.org/2024.arabicnlp-1.24.bib | @inproceedings{khondaker-etal-2024-benchmarking,
title = "Benchmarking {LL}a{MA}-3 on {A}rabic Language Generation Tasks",
author = "Khondaker, Md Tawkat Islam and
Naeem, Numaan and
Khan, Fatimah and
Elmadany, AbdelRahim and
Abdul-Mageed, Muhammad",
editor = "Habash, Nizar and
... | Open-sourced large language models (LLMs) have exhibited remarkable performance in a variety of NLP tasks, often catching up with the closed-sourced LLMs like ChatGPT. Among these open LLMs, LLaMA-3-70B has emerged as the most recent and the most prominent one. However, how LLaMA-3-70B would situate itself in multiling... | [
"Khondaker, Md Tawkat Islam",
"Naeem, Numaan",
"Khan, Fatimah",
"Elmadany, AbdelRahim",
"Abdul-Mageed, Muhammad"
] | Benchmarking {LL}a{MA}-3 on {A}rabic Language Generation Tasks | arabicnlp-1.24 | Poster | 2205.10687v1 |
https://aclanthology.org/2024.arabicnlp-1.25.bib | @inproceedings{saeed-etal-2024-nile,
title = "From Nile Sands to Digital Hands: Machine Translation of {C}optic Texts",
author = "Saeed, Muhammed and
Mohamed, Asim and
Mohamed, Mukhtar and
Shehata, Shady and
Abdul-Mageed, Muhammad",
editor = "Habash, Nizar and
Bouamor, Hou... | The Coptic language, rooted in the historical landscapes of Egypt, continues to serve as a vital liturgical medium for the Coptic Orthodox and Catholic Churches across Egypt, North Sudan, Libya, and the United States, with approximately ten million speakers worldwide. However, the scarcity of digital resources in Copti... | [
"Saeed, Muhammed",
"Mohamed, Asim",
"Mohamed, Mukhtar",
"Shehata, Shady",
"Abdul-Mageed, Muhammad"
] | From Nile Sands to Digital Hands: Machine Translation of {C}optic Texts | arabicnlp-1.25 | Poster | 1912.05082v3 |
https://aclanthology.org/2024.arabicnlp-1.26.bib | @inproceedings{aljabari-etal-2024-event,
title = "Event-Arguments Extraction Corpus and Modeling using {BERT} for {A}rabic",
author = "Aljabari, Alaa and
Duaibes, Lina and
Jarrar, Mustafa and
Khalilia, Mohammed",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ram... | Event-argument extraction is a challenging task, particularly in Arabic due to sparse linguistic resources. To fill this gap, we introduce the corpus (550k tokens) as an extension of Wojood, enriched with event-argument annotations. We used three types of event arguments: $agent$, $location$, and $date$, which we annot... | [
"Aljabari, Alaa",
"Duaibes, Lina",
"Jarrar, Mustafa",
"Khalilia, Mohammed"
] | Event-Arguments Extraction Corpus and Modeling using {BERT} for {A}rabic | arabicnlp-1.26 | Poster | 2004.14135v1 |
https://aclanthology.org/2024.arabicnlp-1.27.bib | @inproceedings{alwajih-etal-2024-dallah,
title = "Dallah: A Dialect-Aware Multimodal Large Language Model for {A}rabic",
author = "Alwajih, Fakhraddin and
Bhatia, Gagan and
Abdul-Mageed, Muhammad",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Na... | Recent advancements have significantly enhanced the capabilities of Multimodal Large Language Models (MLLMs) in generating and understanding image-to-text content. Despite these successes, progress is predominantly limited to English due to the scarcity of high-quality multimodal resources in other languages. This limi... | [
"Alwajih, Fakhraddin",
"Bhatia, Gagan",
"Abdul-Mageed, Muhammad"
] | Dallah: A Dialect-Aware Multimodal Large Language Model for {A}rabic | arabicnlp-1.27 | Poster | 2407.18129v2 |
https://aclanthology.org/2024.arabicnlp-1.28.bib | @inproceedings{bashendy-etal-2024-qaes,
title = "{QAES}: First Publicly-Available Trait-Specific Annotations for Automated Scoring of {A}rabic Essays",
author = "Bashendy, May and
Albatarni, Salam and
Eltanbouly, Sohaila and
Zahran, Eman and
Elhuseyin, Hamdo and
Elsayed, Tamer... | Automated Essay Scoring (AES) has emerged as a significant research problem within natural language processing, providing valuable support for educators in assessing student writing skills. In this paper, we introduce QAES, the first publicly available trait-specific annotations for Arabic AES, built on the Qatari Corp... | [
"Bashendy, May",
"Albatarni, Salam",
"Eltanbouly, Sohaila",
"Zahran, Eman",
"Elhuseyin, Hamdo",
"Elsayed, Tamer",
"Massoud, Walid",
"Bouamor, Houda"
] | {QAES}: First Publicly-Available Trait-Specific Annotations for Automated Scoring of {A}rabic Essays | arabicnlp-1.28 | Poster | 2407.11212v1 |
https://aclanthology.org/2024.arabicnlp-1.29.bib | @inproceedings{ferhat-etal-2024-functional,
title = "Functional Text Dimensions for {A}rabic Text Classification",
author = "Ferhat, Zeyd and
Betka, Abir and
Barka, Riyadh and
Kahhoul, Zineddine and
Boutiba, Selma and
Tiar, Mohamed and
Dahmani, Habiba and
Abdelal... | Text classification is of paramount importance in a wide range of applications, including information retrieval, extraction and sentiment analysis. The challenge of classifying and labelling text genres, especially in web-based corpora, has received considerable attention. The frequent absence of unambiguous genre info... | [
"Ferhat, Zeyd",
"Betka, Abir",
"Barka, Riyadh",
"Kahhoul, Zineddine",
"Boutiba, Selma",
"Tiar, Mohamed",
"Dahmani, Habiba",
"Abdelali, Ahmed"
] | Functional Text Dimensions for {A}rabic Text Classification | arabicnlp-1.29 | Poster | 2006.11586v1 |
https://aclanthology.org/2024.arabicnlp-1.30.bib | @inproceedings{khalilia-etal-2024-arabicnlu,
title = "{A}rabic{NLU} 2024: The First {A}rabic Natural Language Understanding Shared Task",
author = "Khalilia, Mohammed and
Malaysha, Sanad and
Suwaileh, Reem and
Jarrar, Mustafa and
Aljabari, Alaa and
Elsayed, Tamer and
Zi... | This paper presents an overview of the Arabic Natural Language Understanding (ArabicNLU 2024) shared task, focusing on two subtasks: Word Sense Disambiguation (WSD) and Location Mention Disambiguation (LMD). The task aimed to evaluate the ability of automated systems to resolve word ambiguity and identify locations men... | [
"Khalilia, Mohammed",
"Malaysha, Sanad",
"Suwaileh, Reem",
"Jarrar, Mustafa",
"Aljabari, Alaa",
"Elsayed, Tamer",
"Zitouni, Imed"
] | {A}rabic{NLU} 2024: The First {A}rabic Natural Language Understanding Shared Task | arabicnlp-1.30 | Poster | 2407.20663v1 |
https://aclanthology.org/2024.arabicnlp-1.31.bib | @inproceedings{wael-etal-2024-pirates,
title = "Pirates at {A}rabic{NLU}2024: Enhancing {A}rabic Word Sense Disambiguation using Transformer-Based Approaches",
author = "Wael, Tasneem and
Elrefai, Eman and
Makram, Mohamed and
Selim, Sahar and
Khoriba, Ghada",
editor = "Habash, Ni... | This paper presents a novel approach to Ara-bic Word Sense Disambiguation (WSD) lever-aging transformer-based models to tackle thecomplexities of the Arabic language. Utiliz-ing the SALMA dataset, we applied severaltechniques, including Sentence Transformerswith Siamese networks and the SetFit frame-work optimized for ... | [
"Wael, Tasneem",
"Elrefai, Eman",
"Makram, Mohamed",
"Selim, Sahar",
"Khoriba, Ghada"
] | Pirates at {A}rabic{NLU}2024: Enhancing {A}rabic Word Sense Disambiguation using Transformer-Based Approaches | arabicnlp-1.31 | Poster | 2104.08110v1 |
https://aclanthology.org/2024.arabicnlp-1.32.bib | @inproceedings{rajpoot-etal-2024-upaya,
title = "Upaya at {A}rabic{NLU} Shared-Task: {A}rabic Lexical Disambiguation using Large Language Models",
author = "Rajpoot, Pawan and
Jindal, Ashvini and
Parikh, Ankur",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
... | Disambiguating a word{'}s intended meaning(sense) in a given context is important in Nat-ural Language Understanding (NLU). WSDaims to determine the correct sense of ambigu-ous words in context. At the same time, LMD(a WSD variation) focuses on disambiguatinglocation mention. Both tasks are vital in Nat-ural Language P... | [
"Rajpoot, Pawan",
"Jindal, Ashvini",
"Parikh, Ankur"
] | Upaya at {A}rabic{NLU} Shared-Task: {A}rabic Lexical Disambiguation using Large Language Models | arabicnlp-1.32 | Poster | 9410029v1 |
https://aclanthology.org/2024.arabicnlp-1.33.bib | @inproceedings{abdel-salam-2024-rematchka,
title = "rematchka at {A}rabic{NLU}2024: Evaluating Large Language Models for {A}rabic Word Sense and Location Sense Disambiguation",
author = "Abdel-Salam, Reem",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Nadi a... | Natural Language Understanding (NLU) plays a vital role in Natural Language Processing (NLP) by facilitating semantic interactions. Arabic, with its diverse morphology, poses a challenge as it allows multiple interpretations of words, leading to potential misunderstandings and errors in NLP applications. In this paper,... | [
"Abdel-Salam, Reem"
] | rematchka at {A}rabic{NLU}2024: Evaluating Large Language Models for {A}rabic Word Sense and Location Sense Disambiguation | arabicnlp-1.33 | Poster | 2104.08110v1 |
https://aclanthology.org/2024.arabicnlp-1.34.bib | @inproceedings{malaysha-etal-2024-arafinnlp,
title = "{A}ra{F}in{NLP} 2024: The First {A}rabic Financial {NLP} Shared Task",
author = "Malaysha, Sanad and
El-Haj, Mo and
Ezzini, Saad and
Khalilia, Mohammed and
Jarrar, Mustafa and
Almujaiwel, Sultan and
Berrada, Ismail ... | The expanding financial markets of the Arab world require sophisticated Arabic NLP tools. To address this need within the banking domain, the Arabic Financial NLP (AraFinNLP) shared task proposes two subtasks: (i) Multi-dialect Intent Detection and (ii) Cross-dialect Translation and Intent Preservation. This shared tas... | [
"Malaysha, Sanad",
"El-Haj, Mo",
"Ezzini, Saad",
"Khalilia, Mohammed",
"Jarrar, Mustafa",
"Almujaiwel, Sultan",
"Berrada, Ismail",
"Bouamor, Houda"
] | {A}ra{F}in{NLP} 2024: The First {A}rabic Financial {NLP} Shared Task | arabicnlp-1.34 | Poster | 2407.09818v1 |
https://aclanthology.org/2024.arabicnlp-1.35.bib | @inproceedings{hariri-abu-farha-2024-smash,
title = "{SMASH} at {A}ra{F}in{NLP}2024: Benchmarking {A}rabic {BERT} Models on the Intent Detection",
author = "Hariri, Youssef and
Abu Farha, Ibrahim",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Nadi and... | The recent growth in Middle Eastern stock markets has intensified the demand for specialized financial Arabic NLP models to serve this sector. This article presents the participation of Team SMASH of The University of Edinburgh in the Multi-dialect Intent Detection task (Subtask 1) of the Arabic Financial NLP (AraFinNL... | [
"Hariri, Youssef",
"Abu Farha, Ibrahim"
] | {SMASH} at {A}ra{F}in{NLP}2024: Benchmarking {A}rabic {BERT} Models on the Intent Detection | arabicnlp-1.35 | Poster | 2405.16482v1 |
https://aclanthology.org/2024.arabicnlp-1.36.bib | @inproceedings{chowdhury-etal-2024-fired,
title = "{F}ired{\_}from{\_}{NLP} at {A}ra{F}in{NLP} 2024: Dual-Phase-{BERT} - A Fine-Tuned Transformer-Based Model for Multi-Dialect Intent Detection in The Financial Domain for The {A}rabic Language",
author = "Chowdhury, Md. and
Chowdhury, Mostak and
Sh... | In the financial industry, identifying user intent from text inputs is crucial for various tasks such as automated trading, sentiment analysis, and customer support. One important component of natural language processing (NLP) is intent detection, which is significant to the finance sector. Limited studies have been co... | [
"Chowdhury, Md.",
"Chowdhury, Mostak",
"Shanto, Anik",
"Murad, Hasan",
"Das, Udoy"
] | {F}ired{\_}from{\_}{NLP} at {A}ra{F}in{NLP} 2024: Dual-Phase-{BERT} - A Fine-Tuned Transformer-Based Model for Multi-Dialect Intent Detection in The Financial Domain for The {A}rabic Language | arabicnlp-1.36 | Poster | 2402.07448v1 |
https://aclanthology.org/2024.arabicnlp-1.37.bib | @inproceedings{elkordi-etal-2024-alexunlp24,
title = "{A}lexu{NLP}24 at {A}ra{F}in{NLP}2024: Multi-Dialect {A}rabic Intent Detection with Contrastive Learning in Banking Domain",
author = "Elkordi, Hossam and
Sakr, Ahmed and
Torki, Marwan and
El-Makky, Nagwa",
editor = "Habash, Nizar a... | Arabic banking intent detection represents a challenging problem across multiple dialects. It imposes generalization difficulties due to the scarcity of Arabic language and its dialects resources compared to English. We propose a methodology that leverages contrastive training to overcome this limitation. We also augme... | [
"Elkordi, Hossam",
"Sakr, Ahmed",
"Torki, Marwan",
"El-Makky, Nagwa"
] | {A}lexu{NLP}24 at {A}ra{F}in{NLP}2024: Multi-Dialect {A}rabic Intent Detection with Contrastive Learning in Banking Domain | arabicnlp-1.37 | Poster | 2405.16482v1 |
https://aclanthology.org/2024.arabicnlp-1.38.bib | @inproceedings{paran-etal-2024-semanticcuetsync,
title = "{S}emantic{C}uet{S}ync at {A}ra{F}in{NLP}2024: Classification of Cross-Dialect Intent in the Banking Domain using Transformers",
author = "Paran, Ashraful and
Shohan, Symom and
Hossain, Md. and
Hossain, Jawad and
Ahsan, Shawly... | Intention detection is a crucial aspect of natural language understanding (NLU), focusing on identifying the primary objective underlying user input. In this work, we present a transformer-based method that excels in determining the intent of Arabic text within the banking domain. We explored several machine learning (... | [
"Paran, Ashraful",
"Shohan, Symom",
"Hossain, Md.",
"Hossain, Jawad",
"Ahsan, Shawly",
"Hoque, Mohammed Moshiul"
] | {S}emantic{C}uet{S}ync at {A}ra{F}in{NLP}2024: Classification of Cross-Dialect Intent in the Banking Domain using Transformers | arabicnlp-1.38 | Poster | 2212.13015v1 |
https://aclanthology.org/2024.arabicnlp-1.39.bib | @inproceedings{nasr-ben-hajhmida-2024-senit,
title = "{SENIT} at {A}ra{F}in{NLP}2024: trust your model or combine two",
author = "Nasr, Abdelmomen and
Ben HajHmida, Moez",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Nadi and
Abu Farha, Ibrahim ... | We describe our submitted system to the 2024 Shared Task on The Arabic Financial NLP (Malaysha et al., 2024). We tackled Subtask 1, namely Multi-dialect Intent Detection. We used state-of-the-art pretrained contextualized text representation models and fine-tuned them according to the downstream task at hand. We starte... | [
"Nasr, Abdelmomen",
"Ben HajHmida, Moez"
] | {SENIT} at {A}ra{F}in{NLP}2024: trust your model or combine two | arabicnlp-1.39 | Poster | 1809.00052v1 |
https://aclanthology.org/2024.arabicnlp-1.40.bib | @inproceedings{fares-touileb-2024-babelbot,
title = "{B}abel{B}ot at {A}ra{F}in{NLP}2024: Fine-tuning T5 for Multi-dialect Intent Detection with Synthetic Data and Model Ensembling",
author = "Fares, Murhaf and
Touileb, Samia",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ra... | This paper presents our results for the Arabic Financial NLP (AraFinNLP) shared task at the Second Arabic Natural Language Processing Conference (ArabicNLP 2024). We participated in the first sub-task, Multi-dialect Intent Detection, which focused on cross-dialect intent detection in the banking domain. Our approach in... | [
"Fares, Murhaf",
"Touileb, Samia"
] | {B}abel{B}ot at {A}ra{F}in{NLP}2024: Fine-tuning T5 for Multi-dialect Intent Detection with Synthetic Data and Model Ensembling | arabicnlp-1.40 | Poster | 2012.01721v2 |
https://aclanthology.org/2024.arabicnlp-1.41.bib | @inproceedings{ramadan-etal-2024-ma,
title = "{MA} at {A}ra{F}in{NLP}2024: {BERT}-based Ensemble for Cross-dialectal {A}rabic Intent Detection",
author = "Ramadan, Asmaa and
Amr, Manar and
Torki, Marwan and
El-Makky, Nagwa",
editor = "Habash, Nizar and
Bouamor, Houda and
E... | Intent detection, also called intent classification or recognition, is an NLP technique to comprehend the purpose behind user utterances. This paper focuses on Multi-dialect Arabic intent detection in banking, utilizing the ArBanking77 dataset. Our method employs an ensemble of fine-tuned BERT-based models, integrating... | [
"Ramadan, Asmaa",
"Amr, Manar",
"Torki, Marwan",
"El-Makky, Nagwa"
] | {MA} at {A}ra{F}in{NLP}2024: {BERT}-based Ensemble for Cross-dialectal {A}rabic Intent Detection | arabicnlp-1.41 | Poster | 2310.19034v1 |
https://aclanthology.org/2024.arabicnlp-1.42.bib | @inproceedings{ashraf-etal-2024-bfci,
title = "{BFCI} at {A}ra{F}in{NLP}2024: Support Vector Machines for {A}rabic Financial Text Classification",
author = "Ashraf, Nsrin and
Nayel, Hamada and
Aldawsari, Mohammed and
Shashirekha, Hosahalli and
Elshishtawy, Tarek",
editor = "Habas... | In this paper, a description of the system submitted by BFCAI team to the AraFinNLP2024 shared task has been introduced. Our team participated in the first subtask, which aims at detecting the customer intents of cross-dialectal Arabic queries in the banking domain. Our system follows the common pipeline of text classi... | [
"Ashraf, Nsrin",
"Nayel, Hamada",
"Aldawsari, Mohammed",
"Shashirekha, Hosahalli",
"Elshishtawy, Tarek"
] | {BFCI} at {A}ra{F}in{NLP}2024: Support Vector Machines for {A}rabic Financial Text Classification | arabicnlp-1.42 | Poster | 1410.4863v1 |
https://aclanthology.org/2024.arabicnlp-1.43.bib | @inproceedings{lichouri-etal-2024-dzfinnlp,
title = "dz{F}in{N}lp at {A}ra{F}in{NLP}: Improving Intent Detection in Financial Conversational Agents",
author = "Lichouri, Mohamed and
Lounnas, Khaled and
Zakaria, Amziane",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ra... | In this paper, we present our dzFinNlp team{'}s contribution for intent detection in financial conversational agents, as part of the AraFinNLP shared task. We experimented with various models and feature configurations, including traditional machine learning methods like LinearSVC with TF-IDF, as well as deep learning ... | [
"Lichouri, Mohamed",
"Lounnas, Khaled",
"Zakaria, Amziane"
] | dz{F}in{N}lp at {A}ra{F}in{NLP}: Improving Intent Detection in Financial Conversational Agents | arabicnlp-1.43 | Poster | 2407.13565v1 |
https://aclanthology.org/2024.arabicnlp-1.44.bib | @inproceedings{hasanain-etal-2024-araieval,
title = "{A}r{AIE}val Shared Task: Propagandistic Techniques Detection in Unimodal and Multimodal {A}rabic Content",
author = "Hasanain, Maram and
Hasan, Md. Arid and
Ahmad, Fatema and
Suwaileh, Reem and
Biswas, Md. Rafiul and
Zaghou... | We present an overview of the second edition of the ArAIEval shared task, organized as part of the ArabicNLP 2024 conference co-located with ACL 2024. In this edition, ArAIEval offers two tasks: (i) detection of propagandistic textual spans with persuasion techniques identification in tweets and news articles, and (ii)... | [
"Hasanain, Maram",
"Hasan, Md. Arid",
"Ahmad, Fatema",
"Suwaileh, Reem",
"Biswas, Md. Rafiul",
"Zaghouani, Wajdi",
"Alam, Firoj"
] | {A}r{AIE}val Shared Task: Propagandistic Techniques Detection in Unimodal and Multimodal {A}rabic Content | arabicnlp-1.44 | Poster | 2407.04247v1 |
https://aclanthology.org/2024.arabicnlp-1.45.bib | @inproceedings{shah-etal-2024-mememind,
title = "{M}eme{M}ind at {A}r{AIE}val Shared Task: Generative Augmentation and Feature Fusion for Multimodal Propaganda Detection in {A}rabic Memes through Advanced Language and Vision Models",
author = "Shah, Uzair and
Biswas, Md. Rafiul and
Agus, Marco an... | Detecting propaganda in multimodal content, such as memes, is crucial for combating disinformation on social media. This paper presents a novel approach for the ArAIEval 2024 shared Task 2 on Multimodal Propagandistic Memes Classification, involving text, image, and multimodal classification of Arabic memes. For text c... | [
"Shah, Uzair",
"Biswas, Md. Rafiul",
"Agus, Marco",
"Househ, Mowafa",
"Zaghouani, Wajdi"
] | {M}eme{M}ind at {A}r{AIE}val Shared Task: Generative Augmentation and Feature Fusion for Multimodal Propaganda Detection in {A}rabic Memes through Advanced Language and Vision Models | arabicnlp-1.45 | Poster | 2408.04540v1 |
https://aclanthology.org/2024.arabicnlp-1.46.bib | @inproceedings{alhabashi-etal-2024-asos,
title = "{ASOS} at {A}r{AIE}val Shared Task: Integrating Text and Image Embeddings for Multimodal Propaganda Detection in {A}rabic Memes",
author = "Alhabashi, Yasser and
Alharbi, Abdullah and
Ahmad, Samar and
Sibaee, Serry and
Nacar, Omer an... | This paper describes our participation in the ArAIEval Shared Task 2024, focusing on Task 2C, which challenges participants to detect propagandistic elements in multimodal Arabic memes. The challenge involves analyzing both the textual and visual components of memes to identify underlying propagandistic messages. Our a... | [
"Alhabashi, Yasser",
"Alharbi, Abdullah",
"Ahmad, Samar",
"Sibaee, Serry",
"Nacar, Omer",
"Ghouti, Lahouari",
"Koubaa, Anis"
] | {ASOS} at {A}r{AIE}val Shared Task: Integrating Text and Image Embeddings for Multimodal Propaganda Detection in {A}rabic Memes | arabicnlp-1.46 | Poster | 2407.01360v1 |
https://aclanthology.org/2024.arabicnlp-1.47.bib | @inproceedings{riyadh-nabhani-2024-mela,
title = "Mela at {A}r{AIE}val Shared Task: Propagandistic Techniques Detection in {A}rabic with a Multilingual Approach",
author = "Riyadh, Md and
Nabhani, Sara",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Nad... | This paper presents our system submitted for Task 1 of the ArAIEval Shared Task on Unimodal (Text) Propagandistic Technique Detection in Arabic. Task 1 involves identifying all employed propaganda techniques in a given text from a set of possible techniques or detecting that no propaganda technique is present. Addition... | [
"Riyadh, Md",
"Nabhani, Sara"
] | Mela at {A}r{AIE}val Shared Task: Propagandistic Techniques Detection in {A}rabic with a Multilingual Approach | arabicnlp-1.47 | Poster | 2407.01360v1 |
https://aclanthology.org/2024.arabicnlp-1.48.bib | @inproceedings{haouhat-etal-2024-modos,
title = "{MODOS} at {A}r{AIE}val Shared Task: Multimodal Propagandistic Memes Classification Using Weighted {SAM}, {CLIP} and {A}rabian{GPT}",
author = "Haouhat, Abdelhamid and
Cherroun, Hadda and
Bellaouar, Slimane and
Nehar, Attia",
editor = "Ha... | Arabic social media platforms are increasingly using propaganda to deceive or influence people. This propaganda is often spread through multimodal content, such as memes. While substantial research has addressed the automatic detection of propaganda in English content, this paper presents the MODOS team{'}s participati... | [
"Haouhat, Abdelhamid",
"Cherroun, Hadda",
"Bellaouar, Slimane",
"Nehar, Attia"
] | {MODOS} at {A}r{AIE}val Shared Task: Multimodal Propagandistic Memes Classification Using Weighted {SAM}, {CLIP} and {A}rabian{GPT} | arabicnlp-1.48 | Poster | 2407.04247v1 |
https://aclanthology.org/2024.arabicnlp-1.49.bib | @inproceedings{abir-oflazer-2024-nullpointer,
title = "Nullpointer at {A}r{AIE}val Shared Task: {A}rabic Propagandist Technique Detection with Token-to-Word Mapping in Sequence Tagging",
author = "Abir, Abrar and
Oflazer, Kemal",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, ... | This paper investigates the optimization of propaganda technique detection in Arabic text, including tweets {\&} news paragraphs, from ArAIEval shared task 1. Our approach involves fine-tuning the AraBERT v2 model with a neural network classifier for sequence tagging.Experimental results show relying on the first token... | [
"Abir, Abrar",
"Oflazer, Kemal"
] | Nullpointer at {A}r{AIE}val Shared Task: {A}rabic Propagandist Technique Detection with Token-to-Word Mapping in Sequence Tagging | arabicnlp-1.49 | Poster | 2407.01360v1 |
https://aclanthology.org/2024.arabicnlp-1.50.bib | @inproceedings{biswas-etal-2024-mememind,
title = "{M}eme{M}ind at {A}r{AIE}val Shared Task: Spotting Persuasive Spans in {A}rabic Text with Persuasion Techniques Identification",
author = "Biswas, Md. Rafiul and
Shah, Zubair and
Zaghouani, Wajdi",
editor = "Habash, Nizar and
Bouamor, H... | This paper focuses on detecting propagandistic spans and persuasion techniques in Arabic text from tweets and news paragraphs. Each entry in the dataset contains a text sample and corresponding labels that indicate the start and end positions of propaganda techniques within the text. Tokens falling within a labeled spa... | [
"Biswas, Md. Rafiul",
"Shah, Zubair",
"Zaghouani, Wajdi"
] | {M}eme{M}ind at {A}r{AIE}val Shared Task: Spotting Persuasive Spans in {A}rabic Text with Persuasion Techniques Identification | arabicnlp-1.50 | Poster | 2408.04540v1 |
https://aclanthology.org/2024.arabicnlp-1.51.bib | @inproceedings{wang-markov-2024-cltl-araieval,
title = "{CLTL} at {A}r{AIE}val Shared Task: Multimodal Propagandistic Memes Classification Using Transformer Models",
author = "Wang, Yeshan and
Markov, Ilia",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh,... | We present the CLTL system designed for the ArAIEval Shared Task 2024 on multimodal propagandistic memes classification in Arabic. The challenge was divided into three subtasks: identifying propagandistic content from textual modality of memes (subtask 2A), from visual modality of memes (subtask 2B), and in a multimoda... | [
"Wang, Yeshan",
"Markov, Ilia"
] | {CLTL} at {A}r{AIE}val Shared Task: Multimodal Propagandistic Memes Classification Using Transformer Models | arabicnlp-1.51 | Poster | 2407.04247v1 |
https://aclanthology.org/2024.arabicnlp-1.52.bib | @inproceedings{labib-etal-2024-cuet,
title = "{CUET}{\_}sstm at {A}r{AIE}val Shared Task: Unimodal (Text) Propagandistic Technique Detection Using Transformer-Based Model",
author = "Labib, Momtazul and
Rahman, Samia and
Murad, Hasan and
Das, Udoy",
editor = "Habash, Nizar and
Bo... | In recent days, propaganda has started to influence public opinion increasingly as social media usage continues to grow. Our research has been part of the first challenge, Unimodal (Text) Propagandistic Technique Detection of ArAIEval shared task at the ArabicNLP 2024 conference, co-located with ACL 2024, identifying s... | [
"Labib, Momtazul",
"Rahman, Samia",
"Murad, Hasan",
"Das, Udoy"
] | {CUET}{\_}sstm at {A}r{AIE}val Shared Task: Unimodal (Text) Propagandistic Technique Detection Using Transformer-Based Model | arabicnlp-1.52 | Poster | 2407.01360v1 |
https://aclanthology.org/2024.arabicnlp-1.53.bib | @inproceedings{zaytoon-etal-2024-alexunlp,
title = "{A}lex{UNLP}-{MZ} at {A}r{AIE}val Shared Task: Contrastive Learning, {LLM} Features Extraction and Multi-Objective Optimization for {A}rabic Multi-Modal Meme Propaganda Detection",
author = "Zaytoon, Mohamed and
El-Makky, Nagwa and
Torki, Marwan"... | The rise of memes as a tool for spreading propaganda presents a significant challenge in the current digital environment. In this paper, we outline our work for the ArAIEval Shared Task2 in ArabicNLP 2024. This study introduces a method for identifying propaganda in Arabic memes using a multimodal system that combines ... | [
"Zaytoon, Mohamed",
"El-Makky, Nagwa",
"Torki, Marwan"
] | {A}lex{UNLP}-{MZ} at {A}r{AIE}val Shared Task: Contrastive Learning, {LLM} Features Extraction and Multi-Objective Optimization for {A}rabic Multi-Modal Meme Propaganda Detection | arabicnlp-1.53 | Poster | 2407.01360v1 |
https://aclanthology.org/2024.arabicnlp-1.54.bib | @inproceedings{shohan-etal-2024-semanticcuetsync,
title = "{S}emantic{C}uet{S}ync at {A}r{AIE}val Shared Task: Detecting Propagandistic Spans with Persuasion Techniques Identification using Pre-trained Transformers",
author = "Shohan, Symom and
Hossain, Md. and
Paran, Ashraful and
Ahsan, Sh... | Detecting propagandistic spans and identifying persuasion techniques are crucial for promoting informed decision-making, safeguarding democratic processes, and fostering a media environment characterized by integrity and transparency. Various machine learning (Logistic Regression, Random Forest, and Multinomial Naive B... | [
"Shohan, Symom",
"Hossain, Md.",
"Paran, Ashraful",
"Ahsan, Shawly",
"Hossain, Jawad",
"Hoque, Mohammed Moshiul"
] | {S}emantic{C}uet{S}ync at {A}r{AIE}val Shared Task: Detecting Propagandistic Spans with Persuasion Techniques Identification using Pre-trained Transformers | arabicnlp-1.54 | Poster | 2407.04247v1 |
https://aclanthology.org/2024.arabicnlp-1.55.bib | @inproceedings{fouad-weeds-2024-sussexai,
title = "{S}ussex{AI} at {A}r{AIE}val Shared Task: Mitigating Class Imbalance in {A}rabic Propaganda Detection",
author = "Fouad, Mary and
Weeds, Julie",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Nadi and
... | In this paper, we are exploring mitigating class imbalancein Arabic propaganda detection. Given amultigenre text which could be a news paragraphor a tweet, the objective is to identify the propagandatechnique employed in the text along withthe exact span(s) where each technique occurs. Weapproach this task as a sequenc... | [
"Fouad, Mary",
"Weeds, Julie"
] | {S}ussex{AI} at {A}r{AIE}val Shared Task: Mitigating Class Imbalance in {A}rabic Propaganda Detection | arabicnlp-1.55 | Poster | 2407.01360v1 |
https://aclanthology.org/2024.arabicnlp-1.56.bib | @inproceedings{zaghouani-etal-2024-fignews,
title = "The {FIGNEWS} Shared Task on News Media Narratives",
author = "Zaghouani, Wajdi and
Jarrar, Mustafa and
Habash, Nizar and
Bouamor, Houda and
Zitouni, Imed and
Diab, Mona and
El-Beltagy, Samhaa and
AbuOdeh, Muha... | We present an overview of the FIGNEWSshared task, organized as part of the Arabic-NLP 2024 conference co-located with ACL2024. The shared task addresses bias and pro-paganda annotation in multilingual news posts.We focus on the early days of the Israel War onGaza as a case study. The task aims to fostercollaboration in... | [
"Zaghouani, Wajdi",
"Jarrar, Mustafa",
"Habash, Nizar",
"Bouamor, Houda",
"Zitouni, Imed",
"Diab, Mona",
"El-Beltagy, Samhaa",
"AbuOdeh, Muhammed"
] | The {FIGNEWS} Shared Task on News Media Narratives | arabicnlp-1.56 | Poster | 2407.09327v1 |
https://aclanthology.org/2024.arabicnlp-1.57.bib | @inproceedings{alemadi-etal-2024-narrative,
title = "Narrative Navigators at {FIGNEWS} 2024 Shared Task: New Frontiers in Bias and Propaganda Annotation Techniques",
author = "AlEmadi, Maryam and
ElMesselmani, Jana and
Bermak, Lyna and
Abdullah, Goumana and
Sharqawi, Esra{'}a and
... | This paper presents our team{'}s contribution to the FIGNEWS 2024 Shared Task, which involved annotating bias and propaganda in news coverage of the Israel-Palestine conflict. We developed comprehensive guidelines and employed a rigorous methodology to analyze 2,200 news posts from several official Facebook accounts of... | [
"AlEmadi, Maryam",
"ElMesselmani, Jana",
"Bermak, Lyna",
"Abdullah, Goumana",
"Sharqawi, Esra{'}a",
"Jrad, Anissa",
"Zouabi, Zied",
"Zaghouani, Wajdi"
] | Narrative Navigators at {FIGNEWS} 2024 Shared Task: New Frontiers in Bias and Propaganda Annotation Techniques | arabicnlp-1.57 | Poster | 2407.09327v1 |
https://aclanthology.org/2024.arabicnlp-1.58.bib | @inproceedings{jafari-etal-2024-dragon,
title = "{DRAGON} at {FIGNEWS} 2024 Shared Task: a Dedicated {RAG} for {O}ctober 7th conflict News",
author = "Jafari, Sadegh and
Mahmoodzadeh, Mohsen and
Nazari, Vanooshe and
Bahmanyar, Razieh and
Burrows, Kathryn",
editor = "Habash, Nizar... | In this study, we present a novel approach to annotating bias and propaganda in social media data by leveraging topic modeling techniques. Utilizing the BERTopic tool, we performed topic modeling on the FIGNEWS Shared-task dataset, which initially comprised 13,500 samples. From this dataset, we identified 35 distinct t... | [
"Jafari, Sadegh",
"Mahmoodzadeh, Mohsen",
"Nazari, Vanooshe",
"Bahmanyar, Razieh",
"Burrows, Kathryn"
] | {DRAGON} at {FIGNEWS} 2024 Shared Task: a Dedicated {RAG} for {O}ctober 7th conflict News | arabicnlp-1.58 | Poster | 2407.09327v1 |
https://aclanthology.org/2024.arabicnlp-1.59.bib | @inproceedings{el-ghawi-etal-2024-lexiconladies,
title = "{L}exicon{L}adies at {FIGNEWS} 2024 Shared Task: Identifying Keywords for Bias Annotation Guidelines of {F}acebook News Headlines on the {I}srael-{P}alestine 2023 War",
author = "El-Ghawi, Yousra and
Marzouk, Abeer and
Khamis, Aya",
edi... | News bias is difficult for humans to identify, but even more so for machines. This is largely due to the lack of linguistically appropriate annotated datasets suitable for use by classifier algorithms. The FIGNEWS Subtask 1: Bias Annotation involved classifying bias through manually annotated 1800 headlines from social... | [
"El-Ghawi, Yousra",
"Marzouk, Abeer",
"Khamis, Aya"
] | {L}exicon{L}adies at {FIGNEWS} 2024 Shared Task: Identifying Keywords for Bias Annotation Guidelines of {F}acebook News Headlines on the {I}srael-{P}alestine 2023 War | arabicnlp-1.59 | Poster | 2407.09327v1 |
https://aclanthology.org/2024.arabicnlp-1.60.bib | @inproceedings{nwesri-etal-2024-uot1,
title = "Uot1 at {FIGNEWS} 2024 Shared Task: Labeling News Bias",
author = "Nwesri, Abdusalam and
Elbaabaa, Mai and
Lashihar, Fatima and
Alalos, Fatma",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Na... | This paper outlines the University of Tripoli{'}s initiative in creating annotation guidelines to detect bias in news articles concerning the Palestinian-Israeli conflict. Our team participated in the Framing of Israeli Gaza News Media Narrative (FIGNEWS 2024) shared task. We developed annotation guidelines to label bi... | [
"Nwesri, Abdusalam",
"Elbaabaa, Mai",
"Lashihar, Fatima",
"Alalos, Fatma"
] | Uot1 at {FIGNEWS} 2024 Shared Task: Labeling News Bias | arabicnlp-1.60 | Poster | 2407.09327v1 |
https://aclanthology.org/2024.arabicnlp-1.61.bib | @inproceedings{abdul-rauf-etal-2024-nlpcolab,
title = "{NLPC}olab at {F}ig{N}ews 2024 Shared Task: Challenges in Bias and Propaganda Annotation for News Media",
author = "Abdul Rauf, Sadaf and
Sarfraz, Huda and
Nauman, Saadia and
Fatima, Arooj and
SadafZiafat, SadafZiafat and
... | In this paper, we present our methodology and findings from participating in the FIGNEWS 2024 shared task on annotating news fragments on the Gaza-Israel war for bias and propaganda detection. The task aimed to refine the FIGNEWS 2024 annotation guidelines and to contribute to the creation of a comprehensive dataset to... | [
"Abdul Rauf, Sadaf",
"Sarfraz, Huda",
"Nauman, Saadia",
"Fatima, Arooj",
"SadafZiafat, SadafZiafat",
"Ishfaq, Momina",
"Suboor, Alishba",
"Afzal, Hammad",
"Latif, Seemab"
] | {NLPC}olab at {F}ig{N}ews 2024 Shared Task: Challenges in Bias and Propaganda Annotation for News Media | arabicnlp-1.61 | Poster | 2407.09327v1 |
https://aclanthology.org/2024.arabicnlp-1.62.bib | @inproceedings{heierli-etal-2024-bias,
title = "Bias Bluff Busters at {FIGNEWS} 2024 Shared Task: Developing Guidelines to Make Bias Conscious",
author = "Heierli, Jasmin and
Pareti, Silvia and
Pareti, Serena and
Lando, Tatiana",
editor = "Habash, Nizar and
Bouamor, Houda and
... | This paper details our participation in the FIGNEWS-2024 shared task on bias and propaganda annotation in Gaza conflict news. Our objectives were to develop robust guidelines and annotate a substantial dataset to enhance bias detection. We iteratively refined our guidelines and used examples for clarity. Key findings i... | [
"Heierli, Jasmin",
"Pareti, Silvia",
"Pareti, Serena",
"L",
"o, Tatiana"
] | Bias Bluff Busters at {FIGNEWS} 2024 Shared Task: Developing Guidelines to Make Bias Conscious | arabicnlp-1.62 | Poster | 2407.09327v1 |
https://aclanthology.org/2024.arabicnlp-1.63.bib | @inproceedings{sadiah-etal-2024-ceasefire,
title = "Ceasefire at {FIGNEWS} 2024 Shared Task: Automated Detection and Annotation of Media Bias Using Large Language Models",
author = "Sadiah, Noor and
Al-Emadi, Sara and
Rahman, Sumaya",
editor = "Habash, Nizar and
Bouamor, Houda and
... | In this paper, we present our approach for FIGNEWS Subtask 1, which focuses on detecting bias in news media narratives about the Israel war on Gaza. We used a Large Language Model (LLM) and prompt engineering, using GPT-3.5 Turbo API, to create a model that automatically flags biased news media content with 99{\%} accu... | [
"Sadiah, Noor",
"Al-Emadi, Sara",
"Rahman, Sumaya"
] | Ceasefire at {FIGNEWS} 2024 Shared Task: Automated Detection and Annotation of Media Bias Using Large Language Models | arabicnlp-1.63 | Poster | 2407.09327v1 |
https://aclanthology.org/2024.arabicnlp-1.64.bib | @inproceedings{solla-etal-2024-sahara,
title = "{S}ahara Pioneers at {FIGNEWS} 2024 Shared Task: Data Annotation Guidelines for Propaganda Detection in News Items",
author = "Solla, Marwa and
Ebrahem, Hassan and
Issa, Alya and
Harmain, Harmain and
Nwesri, Abdusalam",
editor = "Ha... | In today{'}s digital age, the spread of propaganda through news channels has become a pressing concern. To address this issue, the research community has organized a shared task on detecting propaganda in news posts. This paper aims to present the work carried out at the University of Tripoli for the development and im... | [
"Solla, Marwa",
"Ebrahem, Hassan",
"Issa, Alya",
"Harmain, Harmain",
"Nwesri, Abdusalam"
] | {S}ahara Pioneers at {FIGNEWS} 2024 Shared Task: Data Annotation Guidelines for Propaganda Detection in News Items | arabicnlp-1.64 | Poster | 2407.09327v1 |
https://aclanthology.org/2024.arabicnlp-1.65.bib | @inproceedings{blqees-etal-2024-biasganda,
title = "{B}ias{G}anda at {FIGNEWS} 2024 Shared Task: A Quest to Uncover Biased Views in News Coverage",
author = "Blqees, Blqees and
Wardi, Al and
Al-Sibani, Malath and
Al-Siyabi, Hiba and
Zidjaly, Najma",
editor = "Habash, Nizar and
... | In this study, we aimed to identify biased language in a dataset provided by the FIGNEWS 2024 committee on the Gaza-Israel war. We classified entries into seven categories: Unbiased, Biased against Palestine, Biased against Israel, Biased against Others, Biased against both Palestine and Israel, Unclear, and Not Applic... | [
"Blqees, Blqees",
"Wardi, Al",
"Al-Sibani, Malath",
"Al-Siyabi, Hiba",
"Zidjaly, Najma"
] | {B}ias{G}anda at {FIGNEWS} 2024 Shared Task: A Quest to Uncover Biased Views in News Coverage | arabicnlp-1.65 | Poster | 2407.09327v1 |
https://aclanthology.org/2024.arabicnlp-1.66.bib | @inproceedings{helal-etal-2024-cyberequity,
title = "The {C}yber{E}quity Lab at {FIGNEWS} 2024 Shared Task: Annotating a Corpus of {F}acebook Posts to Label Bias and Propaganda in {G}aza-{I}srael War Coverage in Five Languages",
author = "Helal, Mohammed and
Jarrar, Radi and
Alkhanafseh, Mohammed ... | This paper presents The{\_}CyberEquity{\_}Lab team{'}s participation in the FIGNEWS 2024 Shared Task (Zaghouani, et al., 2024). The task is to annotate a corpus of Facebook posts into bias and propaganda in covering the Gaza-Israel war. The posts represent news articles written in five different languages. The paper pr... | [
"Helal, Mohammed",
"Jarrar, Radi",
"Alkhanafseh, Mohammed",
"Karakra, Abdallah",
"Awadallah, Ruba"
] | The {C}yber{E}quity Lab at {FIGNEWS} 2024 Shared Task: Annotating a Corpus of {F}acebook Posts to Label Bias and Propaganda in {G}aza-{I}srael War Coverage in Five Languages | arabicnlp-1.66 | Poster | 2407.09327v1 |
https://aclanthology.org/2024.arabicnlp-1.67.bib | @inproceedings{ruiz-fernandez-etal-2024-bsc,
title = "{BSC}-{LANGTECH} at {FIGNEWS} 2024 Shared Task: Exploring Semi-Automatic Bias Annotation using Frame Analysis",
author = "Ruiz-Fern{\'a}ndez, Valle and
Saiz, Jos{\'e} and
Gonzalez-Agirre, Aitor",
editor = "Habash, Nizar and
Bouamor, ... | This paper introduces the methodology of BSC-LANGTECH team for the FIGNEWS 2024 Shared Task on News Media Narratives. Following the bias annotation subtask, we apply the theory and methods of framing analysis to develop guidelines to annotate bias in the corpus provided by the task organizators. The manual annotation o... | [
"Ruiz-Fern{\\'a}ndez, Valle",
"Saiz, Jos{\\'e}",
"Gonzalez-Agirre, Aitor"
] | {BSC}-{LANGTECH} at {FIGNEWS} 2024 Shared Task: Exploring Semi-Automatic Bias Annotation using Frame Analysis | arabicnlp-1.67 | Poster | 2407.09327v1 |
https://aclanthology.org/2024.arabicnlp-1.68.bib | @inproceedings{khatib-etal-2024-groningenannotatesgaza,
title = "{G}roningen{A}nnotates{G}aza at the {FIGNEWS} 2024 Shared Task: Analyzing Bias in Conflict Narratives",
author = "Khatib, Khalid and
Gemelli, Sara and
Heisterborg, Saskia and
Majumdar, Pritha and
Minnema, Gosse and
... | In this paper we report the development of our annotation methodology for the shared task FIGNEWS 2024. The objective of the shared task is to look into the layers of bias in how the war on Gaza is represented in media narrative. Our methodology follows the prescriptive paradigm, in which guidelines are detailed and re... | [
"Khatib, Khalid",
"Gemelli, Sara",
"Heisterborg, Saskia",
"Majumdar, Pritha",
"Minnema, Gosse",
"Muti, Arianna",
"Solissa, Noa"
] | {G}roningen{A}nnotates{G}aza at the {FIGNEWS} 2024 Shared Task: Analyzing Bias in Conflict Narratives | arabicnlp-1.68 | Poster | 2407.09327v1 |
https://aclanthology.org/2024.arabicnlp-1.69.bib | @inproceedings{duaibes-etal-2024-sina,
title = "Sina at {F}ig{N}ews 2024: Multilingual Datasets Annotated with Bias and Propaganda.",
author = "Duaibes, Lina and
Jaber, Areej and
Jarrar, Mustafa and
Qadi, Ahmad and
Qandeel, Mais",
editor = "Habash, Nizar and
Bouamor, Houda... | The proliferation of bias and propaganda onsocial media is an increasingly significant concern,leading to the development of techniquesfor automatic detection. This article presents amultilingual corpus of 12, 000 Facebook postsfully annotated for bias and propaganda. Thecorpus was created as part of the FigNews2024 Sh... | [
"Duaibes, Lina",
"Jaber, Areej",
"Jarrar, Mustafa",
"Qadi, Ahmad",
"Q",
"eel, Mais"
] | Sina at {F}ig{N}ews 2024: Multilingual Datasets Annotated with Bias and Propaganda. | arabicnlp-1.69 | Poster | 2407.09327v1 |
https://aclanthology.org/2024.arabicnlp-1.70.bib | @inproceedings{al-mamari-etal-2024-squad,
title = "{SQU}ad at {FIGNEWS} 2024 Shared Task: Unmasking Bias in Social Media Through Data Analysis and Annotation",
author = "Al-Mamari, Asmahan and
Al-Farsi, Fatma and
Zidjaly, Najma",
editor = "Habash, Nizar and
Bouamor, Houda and
Esk... | This paper is a part of the FIGNEWS 2024 Datathon Shared Task and it aims to investigate bias and double standards in media coverage of the Gaza-Israel 2023-2024 conflict through a comprehensive analysis of news articles. The methodology integrated both manual labeling as well as the application of a natural language p... | [
"Al-Mamari, Asmahan",
"Al-Farsi, Fatma",
"Zidjaly, Najma"
] | {SQU}ad at {FIGNEWS} 2024 Shared Task: Unmasking Bias in Social Media Through Data Analysis and Annotation | arabicnlp-1.70 | Poster | 2407.09327v1 |
https://aclanthology.org/2024.arabicnlp-1.71.bib | @inproceedings{saleh-etal-2024-justiceleague,
title = "{J}ustice{L}eague at {FIGNEWS} 2024 Shared Task: Innovations in Bias Annotation",
author = "Saleh, Amr and
Mohamed, Huda and
Sayed, Hager",
editor = "Habash, Nizar and
Bouamor, Houda and
Eskander, Ramy and
Tomeh, Nadi ... | In response to the evolving media representation of the Gaza-Israel conflict, this study aims to categorize news articles based on their bias towards specific entities. Our primary objective is to annotate news articles with labels that indicate their bias: {``}Unbiased{''}, {``}Biased against Palestine{''}, {``}Biased... | [
"Saleh, Amr",
"Mohamed, Huda",
"Sayed, Hager"
] | {J}ustice{L}eague at {FIGNEWS} 2024 Shared Task: Innovations in Bias Annotation | arabicnlp-1.71 | Poster | 2407.09327v1 |
https://aclanthology.org/2024.arabicnlp-1.72.bib | @inproceedings{chan-etal-2024-eagles,
title = "Eagles at {FIGNEWS} 2024 Shared Task: A Context-informed Prescriptive Approach to Bias Detection in Contentious News Narratives",
author = "Chan, Amanda and
A.Baddar, Mai and
Baazaoui, Sofien",
editor = "Habash, Nizar and
Bouamor, Houda an... | This research paper presents an in-depth examination of bias identification in media content related to the Israel-Palestine war. Focusing on the annotation guidelines and process developed by our team of researchers, the document outlines a systematic approach to discerning bias in articles. Through meticulous analysi... | [
"Chan, Am",
"a",
"A.Baddar, Mai",
"Baazaoui, Sofien"
] | Eagles at {FIGNEWS} 2024 Shared Task: A Context-informed Prescriptive Approach to Bias Detection in Contentious News Narratives | arabicnlp-1.72 | Poster | 2407.09327v1 |
https://aclanthology.org/2024.arabicnlp-1.73.bib | @inproceedings{bourahouat-amer-2024-guidelines,
title = "The Guidelines Specialists at {FIGNEWS} 2024 Shared Task: An annotation guideline to Unravel Bias in News Media Narratives Using a Linguistic Approach",
author = "Bourahouat, Ghizlane and
Amer, Samar",
editor = "Habash, Nizar and
Bouamor... | This article presents the participation of {``}The Guideline Specialists{''} in the FIGNEWS 2024 Shared Task, which aims to unravel bias and propaganda in news media narratives surrounding the Gaza-Israel 2023-2024 war. Leveraging innovative annotation methodologies and drawing on a diverse team of annotators, our appr... | [
"Bourahouat, Ghizlane",
"Amer, Samar"
] | The Guidelines Specialists at {FIGNEWS} 2024 Shared Task: An annotation guideline to Unravel Bias in News Media Narratives Using a Linguistic Approach | arabicnlp-1.73 | Poster | 2407.18147v1 |
https://aclanthology.org/2024.arabicnlp-1.74.bib | @inproceedings{alshammari-etal-2024-ksaa,
title = "{KSAA}-{CAD} Shared Task: Contemporary {A}rabic Dictionary for Reverse Dictionary and Word Sense Disambiguation",
author = "Alshammari, Waad and
Almazrua, Amal and
Al Wazrah, Asma and
Almatham, Rawan and
Alhoshan, Muneera and
... | This paper outlines the KSAA-CAD shared task, highlighting the Contemporary Arabic Language Dictionary within the scenario of developing a Reverse Dictionary (RD) system and enhancing Word Sense Disambiguation (WSD) capabilities. The first KSAA-RD (Al-Matham et al., 2023) highlighted significant gaps in the domain of R... | [
"Alshammari, Waad",
"Almazrua, Amal",
"Al Wazrah, Asma",
"Almatham, Rawan",
"Alhoshan, Muneera",
"Alosaimy, Abdulrahman"
] | {KSAA}-{CAD} Shared Task: Contemporary {A}rabic Dictionary for Reverse Dictionary and Word Sense Disambiguation | arabicnlp-1.74 | Poster | 0806.2581v1 |
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