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 16

End-to-End Latency-Minimizing and Load-Balanced Request Scheduling for Edge LLM Inference in Agentic AI Services

arXiv:2609.17193v1 Announce Type: new Abstract: Large language model (LLM)-powered agentic AI services increasingly demand low-latency inference, motivating the deployment of LLMs across distributed...

By Zhen Li, Jun Cai, Haoran Gao, An Li, Tan Li

llms agents efficiency

arXiv AI

Sep 16

Never Stop Thinking: Continuous-Time Language Agents

arXiv:2609.17416v1 Announce Type: new Abstract: Voice agents built on LLMs follow a rigid listen-think-speak loop that inserts seconds of dead air before every reply. We show that continuous-time cog...

By Bojie Li, Noah Shi

llms agents reinforcement-learning

arXiv AI

Sep 16

Transformer-Based Token Fusion and Dynamic Graph Planning for Audio-Visual Navigation

arXiv:2609.17421v1 Announce Type: new Abstract: Audio-Visual Navigation (AVN) requires an agent to localize and navigate toward a continuously vocalizing target relying solely on visual observations...

By Shaohang Wu, Yinfeng Yu

llms agents multimodal

arXiv AI

Sep 16

JustFit: 200K-Token LLM Serving on a 24 GiB Laptop with Just-in-Time State Management

arXiv:2609.17475v1 Announce Type: new Abstract: Capable open-weight models make local coding and reasoning attractive, but their context and execution state strain laptop memory. We present JustFit,...

By Yuhua Chen

llms efficiency multimodal

arXiv AI

Sep 16

Retrieval-Driven Memory Reconsolidation for Long-Term LLM Agents

arXiv:2609.16053v1 Announce Type: cross Abstract: Long-term memory is essential for LLM-based agents operating over extended interactions. Existing memory systems primarily update memory when new inf...

By Yuanyi Song, Yukai Wang, Xinbei Ma, Zhihui Fu, Jianghao Lin, Weiwen Liu, Jun Wang, Huarong Deng, Yong Yu, Weinan Zhang

llms agents benchmarks

arXiv AI

Sep 16

Causal neural set filtering for online multi-target tracking

arXiv:2609.16054v1 Announce Type: cross Abstract: Transformer-based multi-target tracking (MTT) jointly learns data association and state estimation, but MT3/Track-MT3-style trackers repeatedly re-en...

By Zhongdi Liu, Huangyu Dai

llms

arXiv AI

Sep 16

Metacognitive Steering: Learning the Structure of Scientific Judgment

arXiv:2609.16245v1 Announce Type: new Abstract: Long-horizon scientific discovery requires agents to alternate between exploration, disciplined execution, and critical reassessment as evidence change...

By Vincent Karpf, Joseph Reth, Eike Gerhardt, Audrey Wang, Anna Butz, Jiehao Xing, Jialing Song, Larry Callahan

llms agents efficiency safety

arXiv AI

Sep 16

The Pain Axis: LLMs Represent Self-Directed Harm and Act to Relieve It

arXiv:2609.16247v1 Announce Type: new Abstract: Large language models sometimes behave in ways resembling human emotional responses, and recent work has identified internal representations that may e...

By Valen Tagliabue, Leonard Dung, Cameron Berg

llms fine-tuning safety

arXiv AI

Sep 16

Attention is All You Need Until You Need Retention

arXiv:2501.09166v2 Announce Type: replace-cross Abstract: Pretrained Transformers keep what they learned in their weights and lose what they observe once a session ends. The first version of this pap...

By M. Murat Yaslioglu

llms agents safety

arXiv AI

Sep 16

ProtoLIP: From Sentence-Level to Object-Level Evidence Disentanglement

arXiv:2609.16284v1 Announce Type: cross Abstract: Query-conditioned vision--language models enable fine-grained interpretation by revealing how visual evidence changes with textual queries. However,...

By Yan Zhu, Yongbo Chen, Zhengming Ding, Rebecca Faust

llms multimodal benchmarks

arXiv AI

Sep 16

Integrating the Analytic Hierarchy Process with Large Language Models for Transparent Multi-Criteria Decision-Making

arXiv:2609.16779v1 Announce Type: new Abstract: LLMs are increasingly employed in a wide range of decision-making tasks. However, the opacity of their internal reasoning makes it difficult to validat...

By Han Zhiguang (IRIT-MELODI, UT3, IPAL), Farah Benamara (IRIT-MELODI, UT3, IPAL), Pascale Zarat\'e (IRIT, UT Capitole, IRIT-ADRIA)

llms benchmarks safety

arXiv AI

Sep 16

Geospatial Metadata Improves Discoverability by Connecting Datasets Across Scientific Disciplines

arXiv:2609.16498v1 Announce Type: cross Abstract: Research data repositories are essential infrastructure for scientific inquiry and for ensuring that datasets follow FAIR (Findable, Accessible, Inte...

By Daniel Ebanks, Devika Jain

llms rag fine-tuning

arXiv AI

Sep 16

Coupled Calibration and Learning: Mitigating Teacher Bias in LLM Distillation without Target-Domain Reward Feedback

arXiv:2609.17474v1 Announce Type: cross Abstract: Large language model (LLM) distillation aims to transfer the capabilities of a powerful teacher to a smaller student. Direct imitation, however, can...

By Haichen Hu, Yuheng Zhang, David Simchi-Levi

llms efficiency safety

arXiv AI

Sep 16

Artificial intelligence and biosecurity: capabilities, threat pathways, and defense-in-depth governance

arXiv:2609.16213v1 Announce Type: new Abstract: Artificial intelligence is reshaping biological research across an increasingly connected digital-to-physical workflow. General-purpose large language...

By Candace S. Y. Chan, Aris Karatzikos, Ilias Georgakopoulos-Soares

llms agents benchmarks safety

arXiv AI

Sep 16

AquiLLM: Evaluating Faithfulness in Open-Weight RAG-LLM Systems for Scientific Research

arXiv:2609.16519v1 Announce Type: new Abstract: Scientific research increasingly relies on large, heterogeneous data sources, motivating interest in retrieval-augmented generation (RAG) systems that...

By Bernie Boscoe, Srinath Saikrishnan, Vikram Seenivasan, Jack Stark, Andrew Lizarraga, Morgan Himes, Jonathan Soriano, PJ Allen, Tuan Do

llms rag benchmarks safety data-engineering

arXiv AI

Sep 16

CoAdapt: An LLM-based Framework for Adaptive Collaborative Perception in IIoT Robotic Swarms

arXiv:2609.16852v1 Announce Type: new Abstract: Industrial IoT environments increasingly deploy autonomous mobile robots for tasks such as material handling, product assembly, or infrastructure inspe...

By Houssam Hajj Hassan (L2S), Antonia Maria Masucci (L2S), Lynda Zitoune (L2S), Salah-Eddine Elayoubi (L2S)

llms agents robotics benchmarks

arXiv AI

Sep 16

The Immutable Past: Formalizing State Mutability and Conflict Resolution in Mutable RAG

arXiv:2609.16073v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) serves as the primary memory architecture for long-horizon autonomous agents. However, treating shared memory as...

By Hamed HaddadPajouh, Amir AmiriTabat

llms rag agents benchmarks

arXiv AI

Sep 16

Coaching Qwen3 Coder 30B to Think Like a CodeClash Arena Agent

arXiv:2609.16096v1 Announce Type: cross Abstract: Large language model coding agents have recently become useful for software tasks, but weaker or open-weight agents still struggle to reliably interp...

By Ivy Ning Zhang

llms agents fine-tuning benchmarks

arXiv AI

Sep 16

SceneBench: A Hierarchical Benchmark for Vision-Language Understanding of 3D Scenes

arXiv:2609.16233v1 Announce Type: cross Abstract: Vision-language models excel at 2D image understanding but remain limited in 3D spatial reasoning. Progress is hindered by limitations in current ben...

By Anubhav Khanal, Prabigya Acharya, Roshni Poudel, Sujan Kapali, Bigyan Bhatta, Pramish Paudel, Francois Rameau, Danda Pani Paudel

llms multimodal benchmarks

arXiv AI

Sep 16

On the Importance of Gating: Memorization vs. In-Context Learning in State Space Models

arXiv:2609.16540v1 Announce Type: cross Abstract: State Space Models (SSMs) have emerged as a compelling alternative to Transformers, enabling sequence modeling with constant memory and linear comput...

By William L. Tong, Aryo Lotfi, Emmanuel Abbe, Kostas Vaggelakos, Vishnu Banna, Etai Littwin, Josh Susskind, Cengiz Pehlevan, Eran Malach

llms

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