Hugging Face Trending Papers

CANDLE: Character-level Arabic Noise Deduplication using Lightweight Encoder

Handling repeated characters in text can be tricky, since they can represent either the correct spelling of a word or informal character elongation often seen in social media posts. We present CANDLE, a lightweight system for character-level Arabic noise deduplication that addresses this challenge without relying on handcrafted rules, dictionaries, or morphological analyzers.

arXiv AI

Jun 19

A Comparative Study of Pretrained Transformer Models for Quranic ASR: Speech Representations, Label Formats, and Dataset Composition

arXiv:2606. 19747v1 Announce Type: new Abstract: Quran Automatic Speech Recognition (ASR) aims to convert Quranic recitation into text, enabling applications such as aided memorisation tools and Quranic search engines.

By Nabil Mosharraf Hossain (Greentech Apps Foundation, United Kingdom), Riasat Islam (Greentech Apps Foundation, United Kingdom, Queen Mary University of London, United Kingdom), Unaizah Obaidellah (University of Malaya, Malaysia)

llms fine-tuning multimodal benchmarks

arXiv AI

2d ago

Jais 2: A Family of Arabic-Centric Open Large Language Models

arXiv:2608. 13580v1 Announce Type: cross Abstract: Jais 2 is a family of Arabic-centric large language models developed jointly by MBZUAI, Cerebras, and Inception, designed to advance Arabic-centric language modeling, with strong performance across the Arabic and culturally grounded benchmarks evaluated in this report.

By Mohamed Anwar, Abed Alhakim Freihat, George Ibrahim, Mostafa Awad, Abdelrahman Sadallah, Gurpreet Gosal, Gokulakrishnan Ramakrishnan, Sarath Chandran, Biswajit Mishra, Rituraj Joshi, Ahmed Frikha, Etienne Goffinet, Abhishek Maiti, Ali El Filali, Sarah AlBarri, Samujjwal Ghosh, Rahul Pal, Parvez Mullah, Awantika Shukla, Sajid siddiki, Samta Kamboj, Onkar Pandit, Sunil Kumar Sahu, AbdelRahman Elbadawy, Amr Mohamed, Ahmad Chamma, Evan Dufraisse, Abdelaziz Bounhar, Dani Bouch, Hadi Abdine, Guokan Shang, Fajri Koto, Yuxia Wang, Zhuohan Xie, Ali Mekky, Rania Elbadry, Sarfraz Ahmad, Momina Ahsan, Omar El Herraoui, Daniil Orel, Hasan Iqbal, Kareem Elzeky, Mervat Abassy, Kareem Elozeiri, Saadeldine Eletter, Farah Atif, Nurdaulet Mukhituly, Haonan Li, Xudong Han, Aaryamonvikram Singh, Zainul Abedien Ahmed Quraishi, Neha Sengupta, Larry Murray, Avraham Sheinin, Joel Hestness, Natalia Vassilieva, Hector Xuguang Ren, Zhengzhong Liu, Michalis Vazirgiannis, Preslav Nakov

llms nlp efficiency benchmarks

arXiv AI

Jun 19

FlowEdit: Associative Memory for Lifelong Pronunciation Adaptation in Flow-Matching TTS

arXiv:2606. 20518v1 Announce Type: new Abstract: Flow-matching text-to-speech systems achieve remarkable zero-shot quality but remain static after deployment: pronunciation errors on out-of-vocabulary proper nouns persist unless the model is retrained.

By Harshit Singh, Ayush Pratap Singh, Nityanand Mathur

rag multimodal benchmarks

arXiv AI

Jun 19

IHUBERT: Vector-Based Semantic Deduplication and Domain-Balanced Pretraining for Persian Resources

arXiv:2606. 20089v1 Announce Type: cross Abstract: Persian pretrained language models (PLMs) are still limited by the scarcity of large-scale, high-quality pretraining corpora and by insufficient evaluation beyond standard classification and NER tasks.

By Arash Ghafouri, Mahdi Firouzmandi, Hossein Saberi, Mohammad Reza Hasani Ahangar

llms nlp benchmarks

Hugging Face Trending Papers

Jul 23

DONDO: Open w2v-BERT Speech-Recognition Base Models for African Languages

We present DONDO, a family of open, permissively licensed automatic speech recognition (ASR) base models for African languages, built on the w2v-BERT 2. 0 self-supervised speech encoder.

fine-tuning multimodal

arXiv Machine Learning

Jun 5

A Survey on Diffusion Language Models

arXiv:2508. 10875v3 Announce Type: replace-cross Abstract: Diffusion Language Models (DLMs) are rapidly emerging as a powerful and promising alternative to the dominant autoregressive (AR) paradigm.

By Tianyi Li, Mingda Chen, Bowei Guo, Zhiqiang Shen

llms diffusion nlp efficiency multimodal benchmarks

arXiv Machine Learning

Aug 11

Embedding Initialization for Unseen Low-resource Languages in Multilingual NMT: A Case Study on Limbum-English Translation

arXiv:2608. 07629v1 Announce Type: cross Abstract: Multilingual neural machine translation models such as NLLB-200 cover 200 languages but leave thousands unsupported, including most Grassfields Bantu languages of Cameroon.

By Samiratu Ntohsi, Neza David Tuyishimire, Anesu Kafesu, Marvin Ogore, Samuel Oluwajunwonlo Babalola, Oche Ankeli

llms rag nlp fine-tuning

arXiv AI

Jul 7

Telescope: Improving Zero Shot Detection of LLM Generated Content By Measuring Token Repetition Probability

arXiv:2607. 04061v1 Announce Type: cross Abstract: Distinguishing Large Language Model (LLM) generated text from human writing is a critical and difficult challenge.

By Christopher Nassif, Josh F. Cooper

llms benchmarks safety

arXiv Machine Learning

Jun 25

Streaming-dLLM: Accelerating Diffusion LLMs via Suffix Pruning and Dynamic Decoding

arXiv:2601. 17917v3 Announce Type: replace Abstract: Diffusion Large Language Models (dLLMs) offer a compelling paradigm for natural language generation, leveraging parallel decoding and bidirectional attention to achieve superior global coherence compared to autoregressive models.

By Zhongyu Xiao, Zhiwei Hao, Jianyuan Guo, Yong Luo, Jia Liu, Jie Xu, Han Hu

llms diffusion efficiency

arXiv AI

Jun 2

Linguistics-Aware Non-Distortionary LLM Watermarking

arXiv:2606. 00613v1 Announce Type: cross Abstract: Watermarking should identify language-model output without degrading quality or limiting verification to the model provider.

By Shinwoo Park, Hyejin Park, Hyeseon An, Yo-Sub Han

llms computer-vision nlp

arXiv Machine Learning

Aug 6

Kathleen Writes: Autoregressive Generation and Data Scaling Without Attention

arXiv:2608. 04678v1 Announce Type: cross Abstract: Papers 1-2 of the Kathleen series showed that a byte-level, attention-free architecture built from a wavetable encoder and multi-scale reverberant state can match strong baselines on classification at ~450-700K parameters, without pretraining.

By George Fountzoulas

llms rag nlp benchmarks

arXiv AI

Jun 2

Mitigating Hallucinations in Large Language Models Via Decoder Layer Skipping

arXiv:2606. 00819v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved strong performance across diverse natural language tasks, yet their outputs often suffer from hallucinations -- content that is misaligned with factual information.

By Hanze Li, Jinhao You, Yichen Guo, Kai Tang, Shuangyang Xie, Xiande Huang

llms benchmarks safety

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