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

Sep 22

Beyond Raw Context Transfer: Representation-based Federated Retrieval-Augmented Generation

arXiv:2609.22162v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) improves the factuality of large language models (LLMs) and vision-language models (VLMs) by grounding generatio...

By Can Peng, Yu Liu, Yingyu Yang, Anjie Le, Yuyuan Liu, Qianye Yang, J. Alison Noble

llms rag nlp multimodal benchmarks

arXiv Machine Learning

Sep 22

Quantifying Hidden Salt for Precision Healthcare: Sodium Assessment via Joint-Factor Retrieval and Chain-of-Thought Inference

arXiv:2609.22171v1 Announce Type: cross Abstract: Precision healthcare, particularly for conditions like hypertension and cardiovascular disease, necessitates monitoring of dietary sodium intake. How...

By Mingyu Huang, Weiqing Min, Yuehui Fang, Yuna He, Shuqiang Jiang

llms rag benchmarks

arXiv Machine Learning

Sep 22

Dissecting Training-Free Uncertainty Estimation in Multimodal Large Language Models

arXiv:2609.22206v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable performance across a wide range of multimodal tasks, yet understanding and quantify...

By Soroush Seifi, Vaggelis Dorovatas, Lin Li, Yarin Gal, Rahaf Aljundi

llms multimodal benchmarks safety

arXiv Machine Learning

Sep 22

Guiding the coarse levels of semantic IDs makes the fine levels learnable

arXiv:2609.22227v1 Announce Type: cross Abstract: Generative retrieval represents each item by a short Semantic ID and casts recommendation as autoregressive generation of that sequence. Because the...

By Bin Wang, Zhengyu Zhang

llms rag nlp reinforcement-learning safety

arXiv Machine Learning

Sep 22

Assessing Adversarial Robustness of Latent Reasoning Models

arXiv:2609.22228v1 Announce Type: cross Abstract: Large language models increasingly rely on long chain-of-thought (CoT) trajectories for complex reasoning, but autoregressive generation brings subst...

By Shaolong Chen, Ang Li, Mingjie Li, Yisen Wang

llms multimodal benchmarks safety

arXiv Machine Learning

Sep 22

Seeing Through Conflicts: Improving Instruction Hierarchy Alignment in Vision-Language Models

arXiv:2609.22234v1 Announce Type: cross Abstract: Instruction hierarchy (IH) alignment teaches language models to prioritize higher-level instructions when inputs conflict. While studied primarily in...

By Nicholas Sansoterra, Zishuo Zheng, Sachin Kumar

llms agents reinforcement-learning multimodal safety

arXiv Machine Learning

Sep 22

Clinical Domain Classification from Medical Transcriptions

arXiv:2609.22734v1 Announce Type: cross Abstract: Clinical domain classification plays an important role in organizing and analyzing large volumes of unstructured medical text. However, medical trans...

By Sravani Pottipati, Lakshmikar R. Polamreddy

llms nlp

arXiv Machine Learning

Sep 22

Scout: Open-World Species Recognition on the Edge

arXiv:2609.22897v1 Announce Type: cross Abstract: Large vision-language models (VLMs) enable recognition beyond a fixed class set, but their computational demands prevent them from running on many ed...

By Mohammad Mehdi Rastikerdar, Hui Guan, Deepak Ganesan

llms agents multimodal

arXiv Machine Learning

Sep 22

Measured Joules, Learned Routes: Learning to Route for Energy-Efficient LLM Serving

arXiv:2609.23085v1 Announce Type: cross Abstract: Large language models (LLMs) and agentic AI systems are creating rapidly growing inference energy demands as model sizes grow and reasoning trajector...

By Muhammad Abdur Rab Siddiqui, Daniela Rojas, Chen Yang, Wenqi Cui, Yuanyuan Shi, Yize Chen

llms agents fine-tuning benchmarks

arXiv Machine Learning

Sep 22

Machine-Interpretable Information: Compiling Documents into Searchable and Readable Protocol States

arXiv:2609.23371v1 Announce Type: cross Abstract: Long-context language models interface with external knowledge through raw natural language. In retrieval-augmented systems, this creates a persisten...

By Yifan Wang, Dejing Dou

llms rag agents

arXiv Machine Learning

Sep 22

PSD: Pseudo Self-Distillation of Memory Representation Capabilities for LLM Agents

arXiv:2609.23449v1 Announce Type: cross Abstract: Memory systems are becoming a core component of LLM agents, but constructing and maintaining memory remains expensive because it relies on repeated c...

By Pirzada Suhail, Menglin Xia, Xuchao Zhang, Mayukh Das, Chetan Bansal, Saravan Rajmohan

llms agents efficiency

arXiv Machine Learning

Sep 22

OSCAR: Order-aware Scoring and Calibration for AI Rankings

arXiv:2609.24128v1 Announce Type: cross Abstract: Judge-specific sensitivity is useful for aggregating pairwise LLM evaluations, but its interpretation depends on which systematic presentation effect...

By You Liu, Yue Liu, Quanchao Lu, Nick Shipilov

llms

arXiv Machine Learning

Sep 22

ServerlessLoRA: Enabling Low-Latency Serverless Multi-LoRA Serving

arXiv:2505.14468v2 Announce Type: replace Abstract: Multi-LoRA (Low-Rank Adaptation) serving allows many specialized LLM variants to share the same base model by attaching lightweight adapters. This...

By Yifan Sui, Hao Wang, Hanfei Yu, Kaiqiang Xu, Yitao Hu, Chen Chen, Jianxun Li, Kai Chen

llms fine-tuning

arXiv Machine Learning

Sep 22

RheOFormer: A generative transformer model for simulation of complex fluids and flows

arXiv:2510.01365v2 Announce Type: replace Abstract: The ability to model mechanics of soft materials under flowing conditions is key in designing and engineering processes and materials with targeted...

By Maedeh Saberi, Amir Barati Farimani, Safa Jamali

llms benchmarks

arXiv Machine Learning

Sep 22

CLARITY: Medical World Model for Guiding Treatment Decisions by Simulating Context-Aware Disease Trajectories

arXiv:2512.08029v4 Announce Type: replace Abstract: Clinical decision-making in oncology requires forecasting how disease evolves under treatment, yet most AI systems remain static predictors that ca...

By Tianxingjian Ding, Yuanhao Zou, Chen Chen, Mubarak Shah, Yu Tian

llms benchmarks

arXiv Machine Learning

Sep 22

Beyond Forgetting: Representation Misdirection Elicits Controllable Side Behaviors and Capabilities

arXiv:2601.21702v4 Announce Type: replace Abstract: We consider Representation Misdirection (RM), a class of large language model (LLM) unlearning methods that achieve forgetting by redirecting the l...

By Tien Dang, The-Hai Nguyen, Dinh Mai Phuong, Nguyen Minh Phuong, Anh Bui, Hoang Thanh-Tung, Le-Minh Nguyen, Naoya Inoue

llms safety

arXiv Machine Learning

Sep 22

CLIP-Powered Domain Generalization and Domain Adaptation: A Comprehensive Survey

arXiv:2504.14280v2 Announce Type: replace-cross Abstract: As machine learning evolves, domain generalization (DG) and domain adaptation (DA) have become crucial for improving model robustness across...

By Jindong Li, Yongguang Li, Yali Fu, Jiahong Liu, Yixin Liu, Menglin Yang, Irwin King

llms fine-tuning multimodal safety

arXiv Machine Learning

Sep 22

HumanAgencyBench: Scalable Evaluation of Human Agency Support in AI Assistants

arXiv:2509.08494v2 Announce Type: replace-cross Abstract: As humans delegate more tasks and decisions to artificial intelligence (AI), we risk losing control of our individual and collective futures....

By Benjamin Sturgeon, Daniel Samuelson, Jacob Haimes, Jacy Reese Anthis

llms reinforcement-learning robotics

arXiv Computation and Language

Sep 22

DeepInstructor: An Agentic AI Instructor for Experience-Driven Idea Evaluation

arXiv:2609.22104v1 Announce Type: new Abstract: As automated scientific discovery advances, Large Language Models (LLMs) can now generate research ideas at an unprecedented scale, shifting the bottle...

By Rongcan Pei, Fang Guo, Qinglin Qi, Qi Zhu, Yun Luo, Jianhao Yan, Minjun Zhu, Qiujie Xie, Dehong Zheng, Yue Zhang

llms agents safety

arXiv Computation and Language

Sep 22

Evaluating Fine-Tuned and Base Language Models in Maternal and Vaccination Healthcare for African Settings

arXiv:2609.22110v1 Announce Type: new Abstract: Background: Large language models (LLMs) can improve healthcare information delivery in low-resource settings but may produce inaccurate or culturally...

By Abdulquddus Ajibade, Oluwaseun Odunsi, Iyinoluwa Animasaun, Chioma Nwakanma-Akanno, Oluwasegun Oguntuase, Oluwafunke Akinbuwa, Abiodun Adereni

llms fine-tuning safety

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