Search: “models”

SchemaMem: Schema-Indexed Recurrent Memory for Delayed State Retrieval

arXiv:2609.33436v1 Announce Type: new Abstract: Attention provides direct access to past representations, but retaining an ever-growing history is costly. Recurrent models bound persistent state, yet

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Research

Scoring the Wrong Question: Readout Failures in Constrained-Option Evaluation

DGX agent

arXiv:2609.33179v1 Announce Type: cross Abstract: Constrained-option scoring reads a model's probabilities for a fixed set of permitted answers, so it returns a score even when the model is about to w

researcharxiv-cs-lg

29 Sept 2026

See, Measure, and Reason: Learning Visually Grounded Reasoning in Pathology

arXiv:2609.34277v1 Announce Type: new Abstract: Pathological assessment relies on recognizing fine-grained visual details in histological images. Vision-language models (VLMs) increasingly support pat

Local Ai

Server-Enforced Watermarking in U-Shaped Split Federated Learning

arXiv:2511.14422v2 Announce Type: replace-cross Abstract: U-shaped split federated learning (U-SFL) enables resource-constrained Internet of Things devices to collaboratively train models with an edge

local-aiarxiv-cs-lg

Share-Borne AI Virus: Memory-Hopping Attacks Across LLM Agents

arXiv:2609.35576v1 Announce Type: cross Abstract: Large language models are increasingly deployed as stateful assistants that retain information across interactions and use tools to read, modify, and

Simulation-Based Quantum System Inference with Neural Posterior Estimation

arXiv:2609.34995v1 Announce Type: cross Abstract: Models of quantum systems faithfully map system parameters to observations, but the inverse problem of parameter inference from measurement data prese

Singularities of Non-negative Matrix Factorization and their application to Bayesian inference

arXiv:2609.34043v1 Announce Type: cross Abstract: Non-negative matrix factorization (NMF) is a singular statistical model whose Bayesian asymptotics are governed by the real log canonical threshold (R

SketchSSM: Write to the Full State, Read from a Compact Sketch

arXiv:2609.33051v1 Announce Type: new Abstract: Hybrid-attention models replace most softmax attention layers with linear attention, reducing KV-cache growth and enabling larger decode batches where r

SpatialSkill: Self-Evolving Skills for Cross-View Spatial Reasoning

arXiv:2609.34124v1 Announce Type: new Abstract: Cross-view spatial reasoning requires a model to align different viewpoints into a coherent spatial representation, yet this ability remains challenging

researcharxiv-cs-cv

STR: Supervised Transcoder Replacement for Reducing Steering Side Effects

arXiv:2609.32519v1 Announce Type: cross Abstract: Model steering can strengthen a target behavior while degrading other useful behaviors. We introduce Supervised Transcoder Replacement (STR) to reduce

SynDORBench: Evaluating LVLM Perceptual Robustness Under Physically Constrained Visibility Conditions

arXiv:2609.31823v1 Announce Type: new Abstract: Large vision-language models (LVLMs) have demonstrated remarkable performance on multimodal reasoning benchmarks, yet their perceptual reliability under

Synergizing Discriminative Exemplars and Self-Refined Experience for MLLM-based In-Context Learning in Medical Diagnosis

arXiv:2603.27737v2 Announce Type: replace Abstract: General Multimodal Large Language Models (MLLMs) often underperform in capturing domain-specific nuances in medical diagnosis, trailing behind fully

Synthetic data for ratemaking: imputation-based methods vs adversarial networks and autoencoders

arXiv:2509.02171v3 Announce Type: replace-cross Abstract: Actuarial ratemaking depends on high-quality data, yet access to such data is often limited by the cost of obtaining new data, privacy concern

Agents

The bigger change is at the low end. At low effort, GPT-6.1 Sol scores 58.1% for $0.21 per task, up from 50.5% for GPT-6 Sol at the same set…

The bigger change is at the low end. At low effort, GPT-6.1 Sol scores 58.1% for 0.21 per task, up from 50.5% for GPT-6 Sol at the same setting. That's the highest score of any model under 0.30 per ta

agentscognition-ai--x

Safety

The Devil is in the Spectrum Bias: Spectrum-Balanced Feature Matching for Robust Representation Distillation

arXiv:2609.34106v1 Announce Type: new Abstract: Large visual foundation models have demonstrated remarkable transferability across a wide range of downstream tasks. To deploy such models efficiently,

safetyarxiv-cs-cv

The Earth in One Gaze: Training-Free Active Focus for UHR Remote Sensing Understanding

arXiv:2609.31747v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) must balance local detail against scene context when interpreting ultra-high-resolution (UHR) remote sensing (R

The Low-Rank Structure of VLA Reinforcement Learning

arXiv:2609.34599v1 Announce Type: new Abstract: Reinforcement learning (RL) is increasingly used to post-train vision-language-action (VLA) models, yet how RL reshapes these policies remains poorly un

ThinkNet: Compact Architecture Selection and Validation-Gated Ensembles for Subject-Independent MI-EEG Decoding

arXiv:2609.33967v1 Announce Type: cross Abstract: Practical assistive and rehabilitative brain--computer interfaces require subject-independent motor-imagery EEG (MI-EEG) decoders that generalize to n

Safety

TRACE: Trajectory-Based Safety Patch Learning for LLM Post-Training Realignment

arXiv:2607.16242v2 Announce Type: replace Abstract: Fine-Tuning-as-a-Service (FTaaS) platforms let users perform supervised fine-tuning (SFT) on customized data, but this pipeline can erode model safe

safetyarxiv-cs-lg

Training and Inference Dynamics of PLDR-LLMs: Row-Map Collapse, Renormalization, and Predictive Reduction

arXiv:2609.34130v1 Announce Type: new Abstract: This monograph develops a unified account of training and inference in Power Law Decoder Representation language models (PLDR-LLMs). Exact finite work i

VEX-Bench: Benchmarking Verification Complexity of LLM-Generated Misinformation

arXiv:2609.35028v1 Announce Type: new Abstract: Large language models (LLMs) have made misinformation inexpensive to produce but not to verify, creating a growing asymmetry in the information ecosyste

Local Ai

'Where Can I Trust You?': Boundary-Aware Evaluation of Surrogate Fidelity

arXiv:2609.32230v1 Announce Type: new Abstract: Surrogate models are commonly evaluated by how often they agree with their teacher model over an evaluation set. Local variation in this agreement is we

local-aiarxiv-cs-lg

WhiteCon: Semi-Supervised Domain Adaptation Regression Through Whitening Transform and Dual Consistency

arXiv:2609.34078v1 Announce Type: new Abstract: Domain adaptation is crucial for addressing distributional shifts that degrade model performance across domains. While most existing research has center

Artificial Analysis launches the Cyber Index Alliance with partners Collinear, IBM, Nvidia, and Vercel to evaluate how AI agents find and fix vulnerabilities (Artificial Analysis)

Artificial Analysis: Artificial Analysis launches the Cyber Index Alliance with partners Collinear, IBM, Nvidia, and Vercel to evaluate how AI agents find and fix vulnerabilities — The Artificial Anal

model-releasestechmeme

Agents

Auditing Latent-Space Monitors for Autonomous Driving

arXiv:2609.30557v1 Announce Type: cross Abstract: Runtime failure monitors can use a model's internal representations to anticipate failures. We audit this monitoring strategy across two autonomous-dr

agentsarxiv-cs-ai

AuthGuard-R: Safety-Compliant Mission Hijacking and Dual-Gate Defense for LLM-Controlled Robots

model-releasesarxiv-cs-ro

arXiv:2609.31110v1 Announce Type: new Abstract: Large language models are increasingly used as high-level planners for mobile robots, robot manipulators, and autonomous vehicles. Recent studies show t

Benchmarking the Connectomes of Caenorhabditis elegans within the Reservoir Computing Framework

arXiv:2609.30508v1 Announce Type: new Abstract: The aim of this work is to examine the connectomes of Caenorhabditis elegans through a computational lens using the reservoir computing framework. Conne

Tutorials

Combining General and Domain-Specific Pretext Tasks for Brain MR Image Segmentation

arXiv:2609.30708v1 Announce Type: cross Abstract: A key challenge in medical image analysis is the scarcity of large annotated datasets for specific populations and diseases. As deep learning models r

tutorialsarxiv-cs-ai

Applications

Cost-Aware Best-LLM Identification using Dueling Feedback

arXiv:2609.30360v1 Announce Type: cross Abstract: Inspired by the problem of identifying the best model from a collection of large language models (LLMs) with heterogeneous querying costs, we formulat

applicationsarxiv-cs-ai

Cross-Backend QIEO: Universal Runtime Portability across OpenMP5, CUDA, HIP, and Multi-Language Interfaces

model-releasesarxiv-cs-cl

arXiv:2609.30914v1 Announce Type: cross Abstract: Quantum-inspired algorithms emulate quantum mechanical principles, such as, superposition, interference, and probabilistic amplitude evolution, on cla

Differentiable RNA Secondary Structure Extraction for Deep Learning

arXiv:2609.30752v1 Announce Type: new Abstract: Many deep learning approaches to RNA secondary structure prediction have recently been proposed. They typically output a weight matrix W where W_{ij} is

researcharxiv-cs-lg

Evidence-Grounded Auditing of Identification Assumptions in Climate-Policy Causal Evaluations

model-releasesarxiv-cs-cl

arXiv:2609.30867v1 Announce Type: new Abstract: Difference-in-differences (DID) studies are widely used to evaluate climate policy, but assessing the evidence supporting their identification assumptio

FedHisto-PAST: Parameter-Efficient Stain-Aware Federated Learning for Cross-Site Lung Histopathology Classification

model-releasesarxiv-cs-ai

arXiv:2609.31150v1 Announce Type: cross Abstract: Cross-site lung histopathology classification must account for stain variation, non-IID client data, missing classes, and the cost of adapting large p

Game Arena: Strategic LLM Evaluation in Competitive Environments

arXiv:2609.31473v1 Announce Type: new Abstract: We introduce Kaggle Game Arena, an open and ever-expanding platform to evaluate large language models (LLMs) through competitive games. Different from s

researcharxiv-cs-ai

Gauss What You Need: Compact Gaussian Splatting Across Scene Scales

arXiv:2609.31248v1 Announce Type: new Abstract: 3D Gaussian Splatting reconstructs a scene as a collection of Gaussian primitives from a set of posed photographs called the capture. The number of prim

Highlight-Then-Summarize: Learning to Compress Evidence for Long-Context Understanding

model-releasesarxiv-cs-ai

arXiv:2609.31382v1 Announce Type: cross Abstract: Long-context understanding requires large language models (LLMs) to reason over lengthy documents, conversations, and code, yet task-relevant evidence

Interpretable-by-Design Descriptor Portfolios Match a 2048-Dimensional Foundation Embedding on Low-Data Molecular Assays

arXiv:2609.30789v1 Announce Type: new Abstract: In low-data structure-activity prediction, the choice of molecular representation can matter more than the choice of predictor, and tabular foundation m

researcharxiv-cs-lg

Introducing Claude Sonnet 5.5 on AWS

model-releasesaws-ml-blog

Claude Sonnet 5.5 is now available on Amazon Bedrock and Claude Platform on AWS. It's a smarter, more efficient Sonnet model for focused coding and knowledge work, with a lower cost per task at faster

Metacognitive Selective Ensemble for Mobile Systems

arXiv:2609.31031v1 Announce Type: new Abstract: Deep ensembles improve robustness in mobile sensing, but repeatedly executing many models over continuous sensor streams is costly. Selecting only a few

researcharxiv-cs-lg

Muslim: A Deployed Arabic Voice AI Platform for Grounded Islamic Knowledge

model-releasesarxiv-cs-cl

arXiv:2609.31511v1 Announce Type: new Abstract: We present Muslim, a production Arabic voice AI platform serving grounded, sourced Islamic knowledge to real users. Beyond a real-time voice pipeline (N

On the Limits of Univariate Deep Learning for Significant Wave Height Forecasting

arXiv:2609.30688v1 Announce Type: cross Abstract: This study conducts a systematic hyperparameter search across five deep learning architectures, DLinear, LSTM, PatchTST, ResAttLstm, and Mamba2, and n

ORCA: Evaluating LLMs on Data Science Code Translation

model-releasesarxiv-cs-ai

arXiv:2609.30749v1 Announce Type: new Abstract: Data Science Code Translation (DSCT) is the process of converting code between data science libraries while preserving functional equivalence and enabli

Agents

Parameters vs. Context: TRACE Fine-Tuning for Robust Retrieval-Augmented Generation

arXiv:2609.30337v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) mitigates knowledge obsolescence and factual hallucination in large language models by introducing external context

agentsarxiv-cs-lg

Predicting Transmembrane Protein Topology from 3D Structure

arXiv:2609.30446v1 Announce Type: new Abstract: This paper presents a novel approach to infer protein topology using the state-of-the-art graph neural network (GNN), SchNet. The model is trained on th

researcharxiv-cs-ai

Qwen 3.8 is a workhorse

model-releasesr-localllama

https://preview.redd.it/23cumykhabsh1.png?width=944&format=png&auto=webp&s=0b1d1c437fc845169f521b31793e2b1325dab0dd Reminder that you can put Qwen 3.8 27B as a subagent and its a workhorse. Pic: using

Qwen next 3.8 and 3.8 27b Vs Sonnet 5.5 low and Sonnet 5.5 medium.

model-releasesr-localllama

Six months ago, a result like this was unthinkable. But now we can say it loud and clear: local models are at the cutting edge, and the gap of just a few months has been confirmed. Personally, I use Q

Qwen3-VL 8B on a laptop vs Opus 5.5 / Sonnet 5 / GPT-5.6 on 137 messy documents: beat GPT-5.6 on tax forms, lost badly on Indian date formats[R]

model-releasesr-machinelearning

I benchmarked Qwen3-VL 8B Instruct (Q4_K_M, Ollama, M5 24GB, ~30s/doc) against Claude Opus 5.5, Sonnet 5 and GPT-5.6 Terra on: - receipts: CORD (Indonesia) and SROIE (Malaysia), 30 each - 20 scanned 1

Safety

T-RoPE: Time-Aware Rotary Position Embedding for Sequential Recommendation

arXiv:2609.30576v1 Announce Type: new Abstract: Large-scale recommenders increasingly adopt the sequential generative recipe behind large language models, bringing the Transformer into recommendation

safetyarxiv-cs-ai