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arXiv:2608.13076v1 Announce Type: new Abstract: Large Language Models (LLMs) have achieved remarkable success in natural language understanding and generation, but their deployment is constrained by h

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Spatial Memory Agent: Experience-Grounded Procedure Memory for Spatial Intelligence

DGX agent

arXiv:2608.12743v1 Announce Type: new Abstract: Spatial intelligence is becoming a foundation for embodied agents, robotic planning, and multimodal assistants. To improve the spatial reasoning ability

model-releasesarxiv-cs-ai

14 Aug 2026

SteerBench-Work: A Benchmark for Agent Steering at Action Boundaries

arXiv:2608.12654v1 Announce Type: new Abstract: Long-running LLM agents act through tools, and a single step can send an email, merge a pull request, or wire a payment. The steering decision is the pr

Structure-preserving uncertainty quantification for GENERIC dynamics

arXiv:2608.12624v1 Announce Type: new Abstract: Structure-preserving machine learning embeds physical structure directly into model architectures, yet uncertainty quantification (UQ) for such hard-con

researcharxiv-cs-lg

Symmetry-Breaking De Novo Crystal Generation via Markovian Jump Diffusion

arXiv:2608.13457v1 Announce Type: new Abstract: Generating crystals has recently attracted significant interest due to their broad applications in materials science. However, existing generative model

researcharxiv-cs-lg

TsuGO: Probing Search Efficiency in LLM Reasoning via Go Life-and-Death Problems

arXiv:2608.13221v1 Announce Type: new Abstract: The evaluation of LLM reasoning is moving from final-answer accuracy to process-level assessment, yet existing methods still fail to capture how models

Understanding Backdoor Vulnerabilities in Vertical Federated Learning: The Gap Between Research and Practice

arXiv:2608.12962v1 Announce Type: new Abstract: Vertical Federated Learning (VFL) enables organizations holding complementary features of shared entities to collaborate and train models. In this setti

Wasserstein Filtering: A Sample Selection Method for Robust Distribution Learning

arXiv:2608.13418v1 Announce Type: cross Abstract: Given a dataset where a portion of the samples are contaminated, our goal is to recover the underlying clean population distribution. To this end, we

A corpus-specific clinical RAG system matches or outperforms newer frontier LLMs on HealthBench

arXiv:2608.12138v1 Announce Type: cross Abstract: General-purpose large language models (LLMs) have recently been reported to match or exceed specialized clinical AI tools on medical benchmarks, but s

Auditing Frame-Level AUC in Weakly Supervised Video Anomaly Detection: Granularity, Resolution, and Scene Bias

model-releasesarxiv-cs-cv

arXiv:2608.11985v1 Announce Type: new Abstract: Frame-level area under the ROC curve (AUC) is the dominant evaluation metric for weakly supervised video anomaly detection (WSVAD). Its standard form me

AWARe: Mitigating Catastrophic Forgetting via Activation-Weighted Adaptive REtention

arXiv:2608.11758v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) exhibit strong generalization and reasoning abilities due to large-scale multimodal pre-training. However, fine

b10413

model-releasesllama-cpp-releases

common : auto-detect spec type from draft GGUF metadata (#26814) common : auto-detect spec type from draft GGUF metadata When -md loads a local draft model without --spec-type, the sidecar inference i

Beyond Trial-and-Error: Agentic Optimization for Image-to-Video Adherence

arXiv:2608.12290v1 Announce Type: cross Abstract: Modern black-box Image-to-Video (I2V) models offer powerful capabilities in automated content creation, yet their lack of fine-grained control and rel

Cross-Corpus Evaluation of Generalizable Vulnerability Detection in IoT Firmware

arXiv:2608.11492v1 Announce Type: cross Abstract: IoT firmware vulnerability detection remains challenging due to heterogeneous firmware ecosystems, resource-constrained platforms, and limitations in

Diagram-MMU: A Multi-Modal Benchmark for Scientific Diagrams

arXiv:2608.12262v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have been growing the capability for scientific writing and collaboration. For example, OpenAI Prism is a fre

Dueling Deep Q-Learning for Intrusion Detection

arXiv:2608.11291v1 Announce Type: cross Abstract: Intrusion detection systems (IDS) and automated systems for detecting and reporting cyber threats, are commonly handled via supervised machine learnin

LLM Router: Rethinking Routing with Prefill Activations

arXiv:2603.20895v3 Announce Type: replace Abstract: Existing routers rely on semantic query features or handcrafted features, which often fail to capture model-specific failures or intrinsic task diff

researcharxiv-cs-cl

Minimax-H3 can generate 42s videos natively on an RTX Pro 6000 in 80 minutes

model-releasesr-stablediffusion

The maximum frame count allowed by the native 'MiniMax H3 Reference to Video' node technically is 1008, even if that's way over the training range of the model, which is 324 frames. But why not try? S

NetlistBench: Evaluating LLM Reliability in SPICE Netlist Recognition and Manipulation

arXiv:2608.12197v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in circuit design workflows, yet their reliability on simulator-facing SPICE netlist recognition an

ODE-Based Transformer Decoders for Iterative Sign Language Translation

arXiv:2608.11352v1 Announce Type: new Abstract: Sign language translation has achieved strong results with Transformer architectures, yet recent improvements largely rely on scaling model capacity at

Physics-Informed Implicit Neural Representations for Improved Myocardial Perfusion MRI Quantification

arXiv:2608.11282v1 Announce Type: cross Abstract: Quantifying myocardial perfusion from cardiac magnetic resonance (CMR) can be achieved by fitting tracer-kinetic models to the dynamic contrast-enhanc

ReXrank: A Public Leaderboard for AI-Powered Radiology Report Generation

arXiv:2411.15122v2 Announce Type: replace-cross Abstract: AI-driven models have demonstrated significant potential in automating radiology report generation for chest X-rays. However, there is no stan

Safety

Stolen LLM Reasoning: How come OpenAI, Anthrophic, Google have the same vulnerabilities?

If you haven't checked the paper: https://arxiv.org/abs/2608.09867 TLDR: the authors show that you can swap out the 'encrypted' reasoning of the biggest model, like Opus, Sol, and put them into weaker

safetyr-localllama

XBridge: Entity-Grounded Latent Bridge for Heterogeneous LLM Communication

arXiv:2608.11676v1 Announce Type: new Abstract: Heterogeneous multi-agent LLM systems, where agents are powered by different model families, can outperform homogeneous configurations by reducing redun

A Streaming Sparse Cholesky Method for Derivative-Informed Gaussian Process Surrogates Within Digital Twin Applications

arXiv:2511.00366v3 Announce Type: replace-cross Abstract: Digital twins are developed to model the behavior of a specific physical asset (or twin), and they can consist of high-fidelity physics-based

researcharxiv-cs-lg

Benchmarking Time Series Generation Methods for Privacy-Preserving Forecasting

arXiv:2608.10891v1 Announce Type: new Abstract: Time series forecasting in privacy-sensitive domains often requires training models on released data rather than original observations. Synthetic time s

CapProbe: Evaluating Detailed Image Captions via Full-Scene Dense Question Answering

model-releasesarxiv-cs-cv

arXiv:2608.11074v1 Announce Type: new Abstract: Evaluating detailed image captions from Vision-Language Models (VLMs) requires going beyond surface-level semantic similarity. Reference-based metrics (

CHORUS: Complementary Experts for High-Coverage Testbench Stimulus Generation

arXiv:2608.10090v1 Announce Type: new Abstract: Large language models (LLMs) have advanced code generation, where executable feedback provides a more reliable learning signal than textual imitation al

Closed-Loop LLM Co-Pilots for Digital Agriculture

arXiv:2608.09949v1 Announce Type: new Abstract: This study evaluates the application of Large Language Models (LLMs) in complex biological systems, evolving from data analysis to autonomous, AI-guided

DSAgentBench: Can Agents Automate End-to-End Data-Science Workflows in Real Computer Environments?

arXiv:2608.10366v1 Announce Type: new Abstract: Real-world data science involves long-horizon workflows that span data wrangling, exploration, modeling, visualization, and validation, and require coor

GLAM: Efficient Continual Learning at Scale via Grouped LoRA Adapter Merging

arXiv:2509.13211v4 Announce Type: replace Abstract: The ability to learn continuously over time remains a major challenge for modern machine learning systems, even in the era of Foundation Models. Whi

Safety

LLMs Encode Their Failures: Predicting Success from Pre-Generation Activations

arXiv:2602.09924v4 Announce Type: replace-cross Abstract: Running LLMs with extended reasoning on every problem is expensive, but determining which inputs actually require additional compute remains c

safetyarxiv-cs-ai

Multi-Granular Rationale-Guided Molecular LLM for Property Prediction

arXiv:2608.10480v1 Announce Type: new Abstract: Large language models (LLMs) are widely applied across chemical tasks, such as molecular property prediction, which underpins drug discovery. Molecular

researcharxiv-cs-ai

No Free Labels: Limitations of LLM-as-a-Judge Without Human Grounding

arXiv:2503.05061v3 Announce Type: replace Abstract: Reliable evaluation of large language models (LLMs) is critical as their deployment rapidly expands, particularly in high-stakes domains such as bus

Safety

Procedural Fairness Failures in RLHF from Preference Averaging

arXiv:2608.10126v1 Announce Type: cross Abstract: Reinforcement Learning from Human Feedback (RLHF) aggregates heterogeneous preferences into a single reward model, assuming preference homogeneity. Wh

safetyarxiv-cs-ai

REAP: Relation-Aware Elicitation and Parsing for Closed-Book Knowledge Base Construction from LLMs

arXiv:2608.10963v1 Announce Type: new Abstract: We present the REAP system for the AKBC Shared Task 2026 on constructing knowledge bases from language models in a closed-book setting, subject to a bud

Temporally Grounded Compositional Camera Motion Understanding via Geometric Knowledge Distillation

arXiv:2608.10932v1 Announce Type: cross Abstract: Understanding camera motion is fundamental to video perception, with applications in spatial intelligence and controllable video generation. Multimoda

Local Ai

Token-Based Detection of Spurious Correlations in Vision Transformers

arXiv:2509.04009v2 Announce Type: replace-cross Abstract: Due to their powerful feature association capabilities, neural network-based computer vision models have the ability to detect and exploit uni

local-aiarxiv-cs-ai

Toward Human Rights Benchmarking for LLMs: A Pilot Methodology

arXiv:2608.10268v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly mediate legal determinations over what human rights are realized, and how. Yet, no evaluation benchmark exis

TRACE: Trustworthy Retrieval-Augmented Conversational Engine

arXiv:2608.10176v1 Announce Type: new Abstract: Public service chatbots are expected to deliver recommendations from an underlying public service directory, while also making sure that the recommendat

What unique, custom QOL upgrades have you given your local agents?

model-releasesr-localllama

Warning: Kinda long post. If you don't like reading, please skip for your own sanity. Also, I've got nothing to sell, just a tinkerer, so I just want to share ideas and learn from you guys too. When I

10 year garbage card for local llms

model-releasesr-localllama

Hello everyone! I like dumb things. I like working with weak computers and microcontrollers. I like the simplicity and low electricity usage. Simply put, the efficiency of a 'dumb' PC. The first tim

A Rigorous Turing Test: a Foundation for Evaluating Artificial General Intelligence

arXiv:2501.17629v2 Announce Type: replace-cross Abstract: Several studies claim that large language models have passed the Turing Test and hence can 'think', yet none follow Turing's original instruct

Advantage-Guided Gate: Reshaping Open-Ended Reasoning for Vision-Based Spatial Intelligence

model-releasesarxiv-cs-cv

arXiv:2608.07987v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have demonstrated significant potential in complex spatial scene understanding and reasoning tasks. However, th

Beyond Pixels: Exploring DOM Downsampling for LLM-Based Web Agents

arXiv:2508.04412v3 Announce Type: replace Abstract: The advent of large language models (LLMs) has sparked an evolution of autonomous web browsing agents: given a web browsing task and serialised user

Biologically Informed Representation Learning for Robust Cross-Center Generalization of MALDI-TOF Mass Spectrometry

arXiv:2608.08182v1 Announce Type: cross Abstract: Machine learning models for MALDI-TOF mass spectrometry have shown considerable promise for clinical microbiology tasks such as microbial identificati

Compiling and Benchmarking Task-State Horizons for Embodied Agents

model-releasesarxiv-cs-ro

arXiv:2608.08036v1 Announce Type: new Abstract: Frontier agentic models are increasingly deployed as high-level planners for long-horizon embodied tasks. Existing robotic benchmarks have advanced long

Counterfactual Benchmarking and Training for Factuality Consistency and Order-Robust Grounded Reasoning in LLMs over Heterogeneous Knowledge

arXiv:2608.07838v1 Announce Type: new Abstract: Large language models (LLMs) have increasingly supported response generation grounded in user-provided knowledge spanning heterogeneous structures. Howe