Natural language processing

Classical and neural NLP: translation, question answering, tokenization and the evaluation of language understanding.

2,700 stories · RSS feed

arXiv AI

Jun 19

Variable-Length Tokenization via Learnable Global Merging for Diffusion Transformers

arXiv:2606. 20076v1 Announce Type: cross Abstract: Latent Diffusion Models (LDMs) have become dominant in visual synthesis, but their quality-compute trade-off is largely constrained by the tokenizer's fixed compression ratio.

By Dong Hoon Lee, Seunghoon Hong

llms diffusion nlp safety

arXiv AI

Jun 19

Detecting Hallucinations for Large Language Model-based Knowledge Graph Reasoning

arXiv:2606. 19351v1 Announce Type: cross Abstract: Knowledge graph (KG) reasoning infers new knowledge from existing facts and is widely applied in question answering, recommendation, and decision support.

By Xinyan Zhu, Yaoqi Liu, Yue Gao, Huadong Ma, Cheng Yang, Chuan Shi

llms nlp benchmarks safety

arXiv AI

Jun 19

Before the Labels: How Dataset Construction Shapes Suicidality Detection in Clinical Text

arXiv:2606. 19637v1 Announce Type: cross Abstract: Clinical NLP increasingly relies on electronic health record (EHR) data to detect suicidal behaviors, treating clinical documentation as more reliable ground truth than social media.

By Priyanshi Garg, Ishita Rao, Jieqiong Ding, Amandalynne Paullada

nlp

arXiv AI

Jun 19

Structuring and Tokenizing Distributed User Interest Context for Generative Recommendation

arXiv:2606. 20554v1 Announce Type: cross Abstract: Generative recommendation is an emerging paradigm that has shown promise in industrial recommendation systems, aiming to predict users' next interactions from their historical behaviors.

By Ruizhong Qiu, Yinglong Xia, Dongqi Fu, Hanqing Zeng, Ren Chen, Xiangjun Fan, Hong Li, Hong Yan, Hanghang Tong

nlp

arXiv AI

Jun 19

AgentFinVQA: A Deployable Multi-Agent Pipeline for Auditable Financial Chart QA

arXiv:2606. 19782v1 Announce Type: new Abstract: Financial chart question answering in regulated settings demands more than accuracy: practitioners must know which answers to trust before acting on them, and many institutions cannot send client data to external model providers.

By Aravind Narayanan, Shaina Raza

llms agents computer-vision nlp

arXiv AI

Jun 19

VitalAgent: A Tool-Augmented Agent for Reactive and Proactive Physiological Monitoring over Wearable Health Data

arXiv:2605. 29483v2 Announce Type: replace Abstract: Wearable devices enable continuous monitoring of physiological signals such as ECG and PPG, but existing mHealth systems are largely limited to task-specific prediction pipelines or reactive question answering over static summaries.

By Di Zhu, Yu Yvonne Wu, Hong Jia, Aaqib Saeed, Vassilis Kostakos, Ting Dang

agents nlp benchmarks

arXiv AI

Jun 19

Optimal Scheduling in a Question-Answering Forum of Knowledge Workers

arXiv:2606. 19759v1 Announce Type: new Abstract: As individuals turn to the Internet to find answers to questions they may have, several Question Answering (QA) forums have evolved, where users knowledgeable in certain topics can contribute their expertise to answering these requests for information.

By Rohit Negi, Mustafa Yilmaz

nlp

arXiv Machine Learning

Jun 19

Scalable Training of Spatially Grounded 2D Vision-Language Models for Radiology

arXiv:2606. 20477v1 Announce Type: cross Abstract: We study how to train visually grounded vision-language models (VLMs) for radiology without manual spatial annotations.

By Yusuf Salcan (Computer Vision Group, University of Freiburg, Germany, CRIION-AI Lab, Freiburg, Germany), Simon Ging (Computer Vision Group, University of Freiburg, Germany, Adaptive & Agentic AI), Robin Schirrmeister (Department of Radiology, Medical Center -- University of Freiburg, Germany), Philipp Arnold (Department of Radiology, Medical Center -- University of Freiburg, Germany), Elmar Kotter (Department of Radiology, Medical Center -- University of Freiburg, Germany), Behzad Bozorgtabar (Adaptive & Agentic AI), Thomas Brox (Computer Vision Group, University of Freiburg, Germany)

llms computer-vision nlp fine-tuning multimodal benchmarks

arXiv AI

Jun 19

Confidence Calibration for Multimodal LLMs: An Empirical Study through Medical VQA

arXiv:2606. 19950v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) show great potential in medical tasks, but their elicited confidence often misaligns with actual accuracy, potentially leading to misdiagnosis or overlooking correct advice.

By Yuetian Du, Yucheng Wang, Ming Kong, Tian Liang, Qiang Long, Bingdi Chen, Qiang Zhu

llms nlp multimodal

arXiv Machine Learning

Jun 19

What Makes Effective Supervision in Latent Chain-of-Thought: An Information-Theoretic Analysis

arXiv:2606. 20075v1 Announce Type: new Abstract: Latent Chain-of-Thought (CoT) internalizes reasoning within continuous hidden states, offering a promising alternative to verbose discrete reasoning traces.

By Xinghao Chen, Chak Tou Leong, Wenjin Guo, Jian Wang, Wenjie Li, Xiaoyu Shen

diffusion nlp

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

arXiv Machine Learning

Jun 19

Group-Sparse Matrix Factorization for Transfer Learning of Word Embeddings

arXiv:2104. 08928v4 Announce Type: replace-cross Abstract: Unstructured text provides decision-makers with a rich data source in many domains, ranging from product reviews in retail to nursing notes in healthcare.

By Kan Xu, Xuanyi Zhao, Hamsa Bastani, Osbert Bastani

rag nlp fine-tuning benchmarks

arXiv Machine Learning

Jun 18

Approximate Structured Diffusion for Sequence Labelling

arXiv:2606. 18856v1 Announce Type: cross Abstract: Sequence labelling, a core task of Natural Language Processing (NLP), consists in assigning each token of an input sentence a label.

By Nicolas Floquet, Joseph Le Roux, Nadi Tomeh

diffusion nlp

arXiv AI

Jun 18

PosterForest: Hierarchical Multi-Agent Collaboration for Scientific Poster Generation

arXiv:2508. 21720v3 Announce Type: replace Abstract: Automating scientific poster generation requires hierarchical document understanding and coherent content-layout planning.

By Jiho Choi, Seojeong Park, Seongjong Song, Hyunjung Shim

agents nlp

arXiv AI

Jun 18

Narrative Theory-Driven LLM Methods for Automatic Story Generation and Understanding: A Survey

arXiv:2602. 15851v2 Announce Type: replace-cross Abstract: Applications of narrative theories using large language models (LLMs) deliver promising methods in automatic story generation and understanding tasks.

By David Y. Liu, Aditya Joshi, Paul Dawson

llms nlp benchmarks

arXiv AI

Jun 18

Retell, Reward, Repeat: Reinforcement Learning for Narrative Theory-Informed Story Retelling

arXiv:2601. 17226v2 Announce Type: replace-cross Abstract: Counterfactual story retelling exposes LLM shortcomings in constrained narrative solution spaces where they can no longer rely on recalling memorised training data.

By David Y. Liu, Xanthe Muston, Dipankar Srirag, Aditya Joshi, Sebastian Sequoiah-Grayson

llms nlp reinforcement-learning fine-tuning

arXiv AI

Jun 18

From Values to Tokens: An LLM-Driven Framework for Context-aware Time Series Forecasting via Symbolic Discretization

arXiv:2508. 09191v2 Announce Type: replace-cross Abstract: Time series forecasting plays a vital role in supporting decision-making across a wide range of critical applications, including energy, healthcare, and finance.

By Xiaoyu Tao, Shilong Zhang, Mingyue Cheng, Daoyu Wang, Tingyue Pan, Bokai Pan, Changqing Zhang, Shijin Wang

llms nlp fine-tuning safety

arXiv AI

Jun 18

WorldLines: Benchmarking and Modeling Long-Horizon Stateful Embodied Agents

arXiv:2606. 18847v1 Announce Type: new Abstract: To assist humans over extended periods in real homes, embodied agents must remember user routines, world states, and past interactions.

By Yehang Zhang, Jianchong Su, Haojian Huang, Yifan Chang, Tianhao Zhou, Xinli Xu, Yingjie Xu, Yinchuan Li, Zexi Li, Ying-Cong Chen

agents nlp robotics benchmarks

arXiv AI

Jun 18

Morpheus: A Morphology-Aware Neural Tokenizer and Word Embedder for Turkish

arXiv:2606. 18717v1 Announce Type: cross Abstract: Turkish is agglutinative: meaning is carried by morphemes, yet the subword tokenizers that drive modern language models split words by corpus statistics, fragmenting semantically loaded suffixes and -- in the case of WordPiece and rule-based analyzers -- failing to decode their output back to the original text.

By Tolga \c{S}akar

llms rag nlp safety

arXiv AI

Jun 18

ARIADNE: Agnostic Routing for Inference-time Adapter DyNamic sElection

arXiv:2606. 19079v1 Announce Type: new Abstract: The increasing deployment of parameter-efficient fine-tuning (PEFT) has led to model ecosystems in which a single backbone is paired with many task-specialized adapters.

By Enrico Cassano, Micha{\l} Brzozowski, Zuzanna Dubanowska, Paolo Mandica, Neo Christopher Chung

llms rag diffusion nlp fine-tuning

Get the daily briefing