Large language models

Model releases, architecture work and prompting research on large language models — from frontier-lab announcements to the arXiv papers behind them.

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arXiv Machine Learning

Jun 24

Harmonic: Hierarchical State Space Models for Efficient Long-Context Language Modeling

arXiv:2606. 24650v1 Announce Type: cross Abstract: We present Harmonic, a hierarchical state space model (SSM) for language modeling.

By Petr Nyoma

llms benchmarks

arXiv Machine Learning

Jun 24

Prediction of Viscoelastic Droplet Impact Dynamics Using a Vision Transformer-Based Approach

arXiv:2606. 23940v1 Announce Type: cross Abstract: Droplet impact on solid surfaces is a complex fluid dynamics problem with applications in spray cooling, inkjet printing, and pharmaceutical processing.

By Diego A. de Aguiar, Cassio M. Oishi

llms computer-vision

arXiv Machine Learning

Jun 24

Reinforcement Learning to Disentangle Multiqubit Quantum States from Partial Observations

arXiv:2406. 07884v3 Announce Type: replace-cross Abstract: Using partial knowledge of a quantum state to control multiqubit entanglement is a largely unexplored paradigm in the emerging field of quantum interactive dynamics with the potential to address outstanding challenges in quantum state preparation and compression, quantum control, and quantum complexity.

By Pavel Tashev, Stefan Petrov, Matthew T. Diaz, Friederike Metz, Alaina M. Green, Norbert M. Linke, Marin Bukov

llms agents reinforcement-learning benchmarks

arXiv Machine Learning

Jun 24

Selective Rotary Position Embedding

arXiv:2511. 17388v3 Announce Type: replace-cross Abstract: Position information is essential for language modeling.

By Sajad Movahedi, Timur Carstensen, Arshia Afzal, Frank Hutter, Antonio Orvieto, Volkan Cevher

llms rag

arXiv AI

Jun 24

IV-CoT: Implicit Visual Chain-of-Thought for Structure-Aware Text-to-Image Generation

arXiv:2606. 24849v1 Announce Type: cross Abstract: Unified multi-modal large language models (MLLMs) have achieved strong text-to-image generation quality, but still struggle with structure-aware prompt following, where object counts, spatial relations, attribute bindings, and coarse layouts must be preserved.

By Zixuan Li, Haokun Lin, Yicheng Xiao, Zhiwei Li, Xinyang Song, Zelong Zheng, Yong He, Heng Yao, Ke Ding, Chao Yu, Chuan Yuan, Qi Li, Zhenan Sun

llms diffusion multimodal

arXiv Machine Learning

Jun 24

A Physics-Informed Fourier-Wavelet Transformer for Multiscale Computational Fluid Dynamics Surrogate Modeling

arXiv:2606. 24696v1 Announce Type: cross Abstract: Physics-informed surrogate models can accelerate computational fluid dynamics simulations.

By Somyajit Chakraborty, Ming Pan, Xizhong Chen

llms benchmarks

arXiv AI

Jun 24

ScaleToT: Generalizing Structured LLM Reasoning for Billion-Scale Low-Activity User Modeling

arXiv:2606. 24605v1 Announce Type: new Abstract: Accurate user modeling often depends on rich interaction histories, which are unavailable for billions of low-activity users.

By Tianbao Ma, Chang Xi, Yichuan Zou, Chengen Li, Linxun Chen, Zilong Lu, Yanan Niu, Zhaojie Liu, Han Li, Kun Gai

llms fine-tuning

arXiv Machine Learning

Jun 24

Bridging Mechanistic Interpretability and Prompt Engineering with Gradient Ascent for Interpretable Persona Control

arXiv:2601. 02896v3 Announce Type: replace Abstract: Controlling emergent behavioral personas (e.

By Harshvardhan Saini, Yiming Tang, Dianbo Liu

llms safety

arXiv Machine Learning

Jun 24

L3Cube-MahaPOS: A Marathi Part-of-Speech Tagging Dataset and BERT Models

arXiv:2606. 24825v1 Announce Type: cross Abstract: Part-of-Speech (POS) tagging is a foundational NLP task underpinning machine translation, information extraction, and syntactic parsing.

By Hariom Ingle, Ronit Ghode, Ishwari Gondkar, Jidnyasa Harad, Raviraj Joshi

llms nlp benchmarks

arXiv AI

Jun 24

When Helpfulness Overrides Causal Caution: Context-Dependent Suppression and Recovery in LLMs

arXiv:2606. 24370v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly integrated into decision-support roles in business and policy contexts.

By Hiroshi Okumura

llms agents benchmarks

arXiv AI

Jun 24

When CQs Go Wrong: Challenges in CQ Verification with OE-Assist

arXiv:2606. 24619v1 Announce Type: new Abstract: Competency Questions (CQs) are the central component of CQ-verification, an established process in which an ontology is evaluated against a set of natural language questions to determine whether the intended purpose of the ontology has been properly modelled.

By Anna Sofia Lippolis, Mohammad Javad Saeedizade, Robin Keskis\"arkk\"a, Aldo Gangemi, Eva Blomqvist, Andrea Giovanni Nuzzolese

llms safety

arXiv AI

Jun 24

ReM-MoA: Reasoning Memory Sustains Mixture-of-Agents Scaling

arXiv:2606. 24437v1 Announce Type: new Abstract: Mixture-of-Agents (MoA) architectures improve inference-time scaling by organizing multiple LLM agents into layered reasoning pipelines.

By Heng Ping, Arijit Bhattacharjee, Peiyu Zhang, Shixuan Li, Wei Yang, Ali Jannesari, Nesreen Ahmed, Paul Bogdan

llms agents efficiency benchmarks

arXiv AI

Jun 24

From Spatial to Spectral: An Efficient, Frequency-Guided Feature Representation Learner for Small Object Detection

arXiv:2606. 23825v1 Announce Type: cross Abstract: Efficient small object detection is bottlenecked by the inherent feature scarcity of tiny targets, which is further aggravated by operations of spatial-domain detectors that indiscriminately discard critical high-frequency details.

By Yuhan Rui, Shihan Qiao, Yibin Lou, Mingxi Yu, Yutong Wan, Yanqiao Chen, Dongsheng Hou, Zhen Cao, Athena Zhuoming Zhong, Qi Hao

llms computer-vision benchmarks

arXiv AI

Jun 24

Poster: Exploring the Limits of Audio-Based Detection of Turkish Phone Call Scams

arXiv:2606. 24523v1 Announce Type: cross Abstract: Scam phone calls exploit vulnerable communities worldwide, yet research on detection has focused almost exclusively on English and other high-resource languages.

By Arda Eren, Micheal Cheung, Youqian Zhang, Grace Ngai, Eugene Yujun Fu

llms multimodal safety

arXiv AI

Jun 24

FlowPipe: LLM-Enhanced Conditional Generative Flow Networks for Data Preparation Pipeline Construction

arXiv:2606. 24679v1 Announce Type: cross Abstract: Data preparation pipelines improve data quality in machine learning by transforming raw tables into learning-ready data through sequential cleaning and feature transformation operators.

By Kunyu Ni, Lei Cao, Jie He, Xiaotong Zhang, Jianfeng Jin, Junyu Dong, Yanwei Yu

llms benchmarks data-engineering

arXiv AI

Jun 24

LemonHarness Technical Report

arXiv:2606. 24311v1 Announce Type: new Abstract: As large language model (LLM) agents are applied to longer tasks, they increasingly modify workspace state across multiple rounds of iteration.

By Kailong Ren, Fubo Sun, Jiachen Liu, Liu Yang, Zimo Yin, Jiaying Li, Congli Yin, Ming He, Yu Huo, Jiawei Liu, Zeping Chen, Yubin Huangfu, Ronghua Li, Yixuan Wu, Xing Su, Yanzhi Xu, Likang Wu, Hongke Zhao, Lei Zhang, Xiaohui Geng, Jianping Fan

llms rag agents

arXiv AI

Jun 24

Mind the Heads: Topological Representation Alignment for Multimodal LLMs

arXiv:2606. 23885v1 Announce Type: cross Abstract: Representation alignment has emerged as an effective approach to improve Multimodal Large Language Models (MLLMs) by regularizing their internal representations toward those of an external vision encoder.

By Davide Caffagni, Alberto Compagnoni, Federico Melis, Sara Sarto, Pier Luigi Dovesi, Mark Granroth-Wilding, Marcella Cornia, Lorenzo Baraldi

llms multimodal benchmarks safety

arXiv AI

Jun 24

FLUX3D: High-Fidelity 3D Gaussian Generation with Diffusion-Aligned Sparse Representation

arXiv:2606. 24874v1 Announce Type: cross Abstract: Sparse voxel representation has emerged as a scalable foundation for image-to-3D Gaussian Splatting (3DGS) generation, yet current methods struggle to preserve high-frequency visual details of input images due to two structural bottlenecks.

By Haorui Ji, Weizhe Liu, Hongdong Li, Hengkai Guo

llms rag diffusion multimodal benchmarks safety

arXiv AI

Jun 24

Deciphering Fingerprints of 3D Molecular Surfaces for Accurate Epitope Prediction

arXiv:2606. 23830v1 Announce Type: cross Abstract: Molecular surfaces encode the geometric and physicochemical patterns that determine antibody-antigen recognition, central to epitope prediction.

By Fang Wu, Weihao Xuan, Jure Leskovec, Yejin Choi, Li Erran Li

llms benchmarks

arXiv AI

Jun 24

MuTRAP: Multi-trigger Trojans Attacking Robot Task Planning Systems

arXiv:2504. 17070v3 Announce Type: replace-cross Abstract: Robots need task planning methods to achieve goals that require more than one action.

By Mohaiminul Al Nahian, Zainab Altaweel, David Reitano, Sabbir Ahmed, Shiqi Zhang, Adnan Siraj Rakin

llms robotics

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