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 AI

Sep 10

Distilling Vision-Language Models for On-Device Fire Understanding

arXiv:2609.05782v1 Announce Type: new Abstract: Vision-language models (VLMs) offer a promising alternative to conventional fire detection systems by reasoning about the semantic context of a scene a...

By Mohammad Kazzazi, Zixuan Liu, Siavash Khajavi

llms fine-tuning efficiency multimodal safety

arXiv AI

Sep 10

Agentic Algorithm Engineering: Improving Shared-Memory Exact Minimum Cuts

arXiv:2609.07204v1 Announce Type: new Abstract: The minimum cut problem for an undirected edge-weighted graph asks us to divide its set of nodes into two blocks while minimizing the weighted sum of t...

By David A. Bader, Adil Chhabra, Ernestine Gro{\ss}mann, Monika Henzinger, Alexander Noe, Christian Schulz

llms agents benchmarks

arXiv AI

Sep 10

What Does an LLM-Agent Leaderboard Rank Actually Compare?

arXiv:2609.07785v1 Announce Type: new Abstract: An LLM-agent leaderboard invites a familiar inference: an agent ranked above another is the better agent. Public evaluation logs may not support that c...

By Wei-Jung Huang

llms agents benchmarks

arXiv AI

Sep 10

BIO-MEMART: Biometric-Aware KV Cache Memory for Multi-User LLM Agents

arXiv:2609.08566v1 Announce Type: new Abstract: KV cache is evolving from a serving optimization into an external memory substrate for long-term LLM agents. In a shared multi-user deployment, however...

By Yanhong Qian, Xuanying He, Qingguo Meng, Shihao Ding, Xingbo Dong, Zhe Jin

llms agents efficiency benchmarks

arXiv AI

Sep 10

MeClear: Cooperative Game-Theoretic Attribution and Risk-Aware Memory Clearance for Long-Horizon LLM Agents

arXiv:2609.09115v1 Announce Type: new Abstract: Long horizon Large Language Model (LLM) agents rely on external memory systems to preserve user preferences and task knowledge across extended interact...

By Boyu Yang, Jiazheng Sun, Zilong Lu, Zhi Qiu, Xin Peng, Jun Zheng

llms agents

arXiv AI

Sep 10

Memory in Deep Time-Series Models

arXiv:2609.06006v1 Announce Type: cross Abstract: Deep learning for time series has progressed through successive architectural paradigms, from recurrent networks and transformers to structured state...

By Minh Hoang Nguyen, Huu Hiep Nguyen, Manh Nguyen, Van Dai Do, Dung Nguyen, Hung Le

llms rag agents

arXiv AI

Sep 10

Flow3D-OPD: Multi-Teacher On-Policy Distillation for 3D Geometry Generation with Flow-Matching Diffusion Transformer

arXiv:2609.07137v1 Announce Type: cross Abstract: Recent image-to-3D generation models built on flow-matching diffusion Transformers (DiT) can produce high-fidelity meshes, yet their post-training st...

By Zhiwei Ning, Zhen Zhou, Puhua Jiang, Xintong Han, Gengming Zhang, Jie Yang, Zhonglong Zheng, Yuanjie Zheng, Wei Liu, Chunchao Guo

llms agents diffusion reinforcement-learning efficiency

arXiv AI

Sep 10

Same Values, Different Languages? From Multilingual Probing to Steering LLMs Toward Chinese Social Values

arXiv:2609.08515v1 Announce Type: cross Abstract: As Large Language Models (LLMs) are increasingly integrated into human society, aligning them with pluralistic social values has become a critical pr...

By Yuemei Xu, Kexin Xu, Jian Zhou, Haoyu Lu, Yequan Wang, Aishan Liu

llms fine-tuning safety

arXiv AI

Sep 10

The Unreliable Progress Bar: Can LLM Agents Reliably Report Task Progress Throughout Execution?

arXiv:2609.08589v1 Announce Type: cross Abstract: Recent large language models can emit task-progress signals that agent frameworks use to decide whether a task should continue or stop, yet whether a...

By Boyang Wang, Yunhan Wang, Yalun Wu

llms agents benchmarks

arXiv AI

Sep 10

Evaluating Steering Techniques using Human Similarity Judgments

arXiv:2505.19333v2 Announce Type: replace Abstract: Current evaluations of Large Language Model (LLM) steering techniques focus on task-specific performance, overlooking how well steered representati...

By Zach Studdiford, Timothy T. Rogers, Siddharth Suresh, Kushin Mukherjee

llms safety

arXiv AI

Sep 10

Large Language Models Transform Organic Synthesis From Reaction Prediction to Automation

arXiv:2508.05427v2 Announce Type: replace Abstract: Large language models (LLMs) are beginning to reshape how organic-synthesis workflows are represented, queried, planned, and connected to experimen...

By Kartar Kumar, Rajesh Kumar, Nikesh Lagun

llms agents robotics multimodal safety

arXiv AI

Sep 10

Behavioral Grammar: Detecting Adaptive Malware via Tiny Language Model Priors and Second-Order Temporal Analysis

arXiv:2608.00745v2 Announce Type: replace Abstract: Modern endpoint detection systems face a fundamental tension: signature-based approaches are trivially evaded by polymorphic or adaptive threats, w...

By Zihan Luo

llms agents safety

arXiv AI

Sep 10

Precision at Scale: Domain-Specific Datasets On-Demand

arXiv:2407.03463v2 Announce Type: replace-cross Abstract: In the realm of self-supervised learning (SSL), conventional wisdom has gravitated towards the utility of massive, general domain datasets fo...

By Jes\'us M Rodr\'iguez-de-Vera, Imanol G Estepa, Ignacio Saras\'ua, Bhalaji Nagarajan, Petia Radeva

llms agents benchmarks

arXiv AI

Sep 10

ChatBEV: Empowering Traffic Scene Understanding and Simulation via Vision-Language Model

arXiv:2503.13938v3 Announce Type: replace-cross Abstract: Comprehensive traffic scene understanding is a foundational capability for Intelligent Transportation Systems (ITS) underpinning applications...

By Qingyao Xu, Ya Zhang, Yanfeng Wang, Siheng Chen

llms fine-tuning multimodal benchmarks

arXiv AI

Sep 10

Beyond Retrieval: Joint Supervision and Multimodal Document Ranking for Textbook Question Answering

arXiv:2505.13520v2 Announce Type: replace-cross Abstract: Textbook question answering (TQA) is a complex task, requiring the interpretation of complex multimodal context. Although recent advances hav...

By Hessa Alawwad, Usman Naseem, Areej Alhothali, Ali Alkhathlan, Amani Jamal

llms rag nlp multimodal safety

arXiv AI

Sep 10

MCANet: A Multi-Scale Class-Specific Attention Network for Multi-Label Post-Hurricane Damage Assessment Using UAV Imagery

arXiv:2509.04757v2 Announce Type: replace-cross Abstract: Hurricanes cause widespread damage to buildings, roads, and other infrastructure, making timely post-disaster damage assessment critical for...

By Zhangding Liu, Neda Mohammadi, John E. Taylor

llms computer-vision

arXiv AI

Sep 10

BETA-Labeling for Multilingual Dataset Construction in Low-Resource IR

arXiv:2602.14488v3 Announce Type: replace-cross Abstract: IR in low-resource languages remains limited by the scarcity of high-quality, task-specific annotated datasets. Manual annotation is expensiv...

By Md. Najib Hasan, Mst. Jannatun Ferdous Rain, Fyad Mohammed, Nazmul Siddique

llms nlp benchmarks safety

arXiv AI

Sep 10

CTC-TTS: LLM-based dual-streaming text-to-speech with CTC alignment

arXiv:2602.19574v2 Announce Type: replace-cross Abstract: Large-language-model (LLM)-based text-to-speech (TTS) systems can generate natural speech, but most are not designed for low-latency dual-str...

By Hanwen Liu, Saierdaer Yusuyin, Hao Huang, Zhijian Ou

llms rag multimodal safety

arXiv Machine Learning

Sep 10

From Narrative to Auditable Forecasts: A Structured Scaffold for Agentic Forecasting

arXiv:2609.05905v1 Announce Type: cross Abstract: LLM agents are increasingly used for live forecasting, where they retrieve up-to-date information and produce estimates for unresolved future events....

By Yuanpu Cao, Yongkang Du, Yurui Chang, Lu Lin, Jinghui Chen

llms agents benchmarks

arXiv AI

Sep 10

FragileFlow: Spectral Control of Correct-but-Fragile Predictions for Foundation Model Robustness

arXiv:2605.08896v2 Announce Type: replace-cross Abstract: Robust adaptation of LLMs and VLMs is often evaluated by average accuracy or average consistency under perturbations. However, these averages...

By Zhuoyun Li, Boxuan Wang, Jinwei Hu, Xiaowei Huang, Yi Dong

llms benchmarks

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