Large language models

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

28,264 stories · RSS feed

arXiv Machine Learning

Oct 5

ChronoSpike: An Adaptive Spiking Graph Neural Network for Dynamic Graphs

arXiv:2602.01124v4 Announce Type: replace Abstract: Dynamic graph representation learning requires capturing both structural relations and temporal evolution, yet existing approaches face a core trad...

By Md Abrar Jahin, Taufikur Rahman Fuad, Jay Pujara, Craig Knoblock

llms efficiency benchmarks safety

arXiv Machine Learning

Oct 5

WakeKV: Reactive, Reversible KV Residency for Heads That Change Their Minds

arXiv:2610.02713v1 Announce Type: cross Abstract: Most KV-cache compression methods classify attention heads once, either offline or during prefill, and keep this classification fixed throughout gene...

By Utkarsh Ranjan

llms efficiency

arXiv AI

Oct 5

Student-Guided Teacher Distillation for Efficient LLM Task Routing: Positioning Against Jev-Style System-1 Classifiers

arXiv:2610.02516v1 Announce Type: cross Abstract: Zero-shot classifiers are useful for routing user requests to specialized LLM tasks, but scoring every request against a large candidate set is expen...

By Haifeng Wu, Srinivasan Manoharan, Jian Wan, Fangbo Tu, Junhua Zhao, Xin Chen

llms rag reinforcement-learning efficiency safety

arXiv AI

Oct 5

OpenGameEval: Benchmarking Agentic Programming and Exploration in a Stateful Game Engine

arXiv:2610.02563v1 Announce Type: cross Abstract: We present OpenGameEval, a benchmark and evaluation framework for agentic game development inside Roblox Studio. It runs language models as agents in...

By Eray Turkel, Mengsha Sun, Kartik Ayyar, Sean Dunigan, Jack Lu, Vlad Shcherban, Hsiang-Shun Shih, Xin Wang, Tiantian Zhang

llms agents benchmarks

arXiv Machine Learning

Oct 5

MintEval: Do LLMs Implement the Trading Strategy You Asked For? A Behavioural-Equivalence Benchmark for Natural-Language-to-Strategy Code

arXiv:2610.03080v1 Announce Type: cross Abstract: Large language models are moving from producing trading signals to writing the code that executes them. The failure mode of the second role is silent...

By Siyu Wang, Yifan Wang, Yuecheng He

llms benchmarks

arXiv Machine Learning

Oct 5

ParaGeo: Decomposing Paralinguistic Variation into a Shared Latent Geometry

arXiv:2610.03125v1 Announce Type: cross Abstract: Speech delivery varies with both the requested paralinguistic attribute and the linguistic content. We introduce ParaGeo, a matched-content decomposi...

By Yuhan Liu, Yuxuan Ou, Ruoxi Su, Mohamed Ahmed Zaki, Yunbo Long

llms benchmarks

arXiv Machine Learning

Oct 5

Does Physics Live in the Activations? Localizing Physical Quantities in Video Diffusion Models

arXiv:2610.03154v1 Announce Type: cross Abstract: Video generation models produce strikingly realistic sequences and are increasingly proposed as world models, yet recent benchmarks reveal pronounced...

By Jonas Kneifl, Jakub Skalski, Bart{\l}omiej Twardowski, Kamil Deja

llms diffusion benchmarks

arXiv Machine Learning

Oct 5

Can AI Understand the Language of Origami?

arXiv:2603.13856v3 Announce Type: replace Abstract: Building AI systems that can plan, act, and create in the physical world requires more than pattern recognition. Such systems must reason about the...

By Naaisha Agarwal, Yihan Wu, Xin Guan, Ayaan Garg, Yikuan Hu, Mohan Li, Vincenzo Collura, Wang-Zhou Dai, Yao-Xiang Ding, Emanuele Sansone

llms multimodal benchmarks

arXiv AI

Oct 5

MuonIO: Principled Norm-Aware Descent for Embedding Tables and Language Model Heads

arXiv:2610.02705v1 Announce Type: cross Abstract: The Muon optimizer derives its update rule for hidden linear layers by solving a local linearization of the loss penalized by the spectral norm, moti...

By Linkai Ma, Xinyu Luo, Mengbo Wang, Ananth Grama, Petros Drineas, Brian Bullins

llms rag

arXiv AI

Oct 5

ConvoDrift: A Multi-Turn Conversational Dataset for Modeling Stylistic Tone Evolution

arXiv:2610.02873v1 Announce Type: cross Abstract: The evolution of linguistic style in conversations is an underexplored issue in NLP. Most style-control datasets focus on sentences or assume a stati...

By Vihindi Kotalawala, Pamoda Dilranga, Gayani Thoradeniya, Prasan Yapa

llms nlp safety

arXiv AI

Oct 5

Fast Models, Slow Evidence: A Paired and Self-Audited Evaluation of System-1 Decision Models for LLM Agent Harnesses

arXiv:2610.02267v1 Announce Type: new Abstract: Agent harnesses make many small, typed decisions per task: which model to call, which tool to use, whether retrieved text is relevant, whether an input...

By Jiawei Li

llms rag agents

arXiv AI

Oct 5

Choosing Before Acting: Comparative Value Estimation for Long-Horizon Tool-Use Agents

arXiv:2610.02330v1 Announce Type: new Abstract: Large language models (LLMs) rely on long-horizon tool invocation sequences for complex tasks, where each invocation can alter the task state and condi...

By Yu Li, Zheng Zhang, Xin Liu, Shengtian Yang, Guangfeng Cai, Lei Feng

llms agents benchmarks

arXiv AI

Oct 5

Tailoring the Quantization Space for 1-Bit KV Cache Compression

arXiv:2610.03027v1 Announce Type: cross Abstract: The key-value (KV) cache becomes a major memory bottleneck in long-context LLM inference, placing substantial pressure on memory capacity and bandwid...

By Minsoo Cheong, Donghyun Son, Sungjoo Yoo

llms efficiency benchmarks

arXiv AI

Oct 5

WebFovea: When the Model Is Right but the Click Is Wrong -- Reliable Round Trips for Vision-Based Web Agents on Live Websites

arXiv:2610.03036v1 Announce Type: cross Abstract: We present WebFovea, a vision-based web agent that placed 2nd in the WebRetriever Challenge 2026 with a final score of 57.0 out of 100. The challenge...

By Jiangang Han

llms agents multimodal benchmarks safety

arXiv Computation and Language

Oct 5

Last Layer Logits to Logic: Empowering LLMs with Logic-Consistent Structured Knowledge Reasoning

arXiv:2511.07910v3 Announce Type: replace Abstract: Large Language Models (LLMs) achieve excellent performance in natural language reasoning tasks through pre-training on vast unstructured text, enab...

By Songze Li, Zhiqiang Liu, Zhaoyan Gong, Xiaoke Guo, Zhongpu Bo, Zhengke Gui, Lei Liang, Huajun Chen, Wen Zhang

llms nlp benchmarks

arXiv Machine Learning

Oct 5

Autoregressive Differentiable Method for Integer Programming

arXiv:2610.02528v1 Announce Type: new Abstract: We introduce an autoregressive differentiable method to solve 0-1 integer programs. We fix an arbitrary order of the binary variables and we train a tr...

By Ouns El Harzli, Yudong Cao

llms benchmarks

arXiv Computation and Language

Oct 5

Specializing Without Forgetting: Analyzing Knowledge Preservation in Multilingual Model Adaptation

arXiv:2606.00284v2 Announce Type: replace Abstract: While continual pretraining (CPT) is a practical way to extend large language models to new languages, na\"ive finetuning often erodes existing cap...

By Sanchit Ahuja, Terra Blevins

llms fine-tuning

arXiv Machine Learning

Oct 5

DISSOLVR: An Interpretable and Fast Framework for Aqueous and Organic Solubility Prediction

arXiv:2610.02574v1 Announce Type: new Abstract: High-fidelity solubility prediction is fundamental to pharmaceutical development and environmental partitioning, where accurate modeling must couple mo...

By Vansh Ramani, Har Ashish Arora, Dhairya Kuchhal, Sayan Ranu, Tarak Karmakar

llms benchmarks safety

arXiv Machine Learning

Oct 5

Activation Sparsity with Weight Approximation for Faster LLM Decoding on Offloaded Weights

arXiv:2610.02598v1 Announce Type: new Abstract: Deploying LLMs on consumer-grade GPUs with insufficient memory to hold their weights can result in prohibitively slow inference, because decoding repea...

By JuneHyung Kim, Sankeerth Durvasula, Nandita Vijaykumar

llms efficiency

arXiv AI

Oct 5

When Numbers Start Talking: Numerical Signalling and Strategic Behaviour Among LLMs

arXiv:2610.03033v1 Announce Type: new Abstract: Large language model (LLM)-based agents increasingly operate in multi-agent systems (MAS) characterised by strategic interaction. However, little is kn...

By Alessio Buscemi, Daniele Proverbio, Alessandro Di Stefano, The Anh Han, German Castignani, Pietro Li\`o

llms agents safety

Get the daily briefing