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Translation Invariance of Neural Operators for the FitzHugh-Nagumo Model

arXiv:2603.17523v2 Announce Type: replace Abstract: Neural operators (NOs) are powerful deep learning frameworks designed to learn solution operators of partial differential equations. This study eval

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Model Releases

TreeThink: A Modular Tree Search Library for Mathematical Reasoning with LLMs

DGX agent

arXiv:2607.11258v2 Announce Type: replace Abstract: Tree search algorithms enable systematic exploration of the proof space in neural theorem proving. Existing LLM tree search libraries primarily targ

model-releasesarxiv-cs-cl

10 Sept 2026

Try this prompt in Claude chat to give it more context about yourself: Interview me in depth using free text, or askuserquestion tool when m…

Try this prompt in Claude chat to give it more context about yourself: Interview me in depth using free text, or askuserquestion tool when multiple choice works, about relevant parts of my life you do

model-releasesthariq--x

TTGBench: Benchmarking Topological Evolution and Semantic Drift in Text-attributed Temporal Graphs

arXiv:2609.08226v1 Announce Type: new Abstract: Temporal graph learning models the evolution of dynamic systems, where both structural interactions and semantic states change over time. However, exist

Two-Token Features and Small-Large Ensembles for VLM Hallucination Detection

arXiv:2609.10244v1 Announce Type: new Abstract: We present our system for the SHROOM-Visions 2026 shared task on character-level VLM hallucination detection. A small (4B-parameter) VLM is fine-tuned a

Typed Federated Artifacts for the Agentic Web:Sharing Tool-Routing Knowledge Across Frozen,Heterogeneous LLM Agents

arXiv:2609.06815v1 Announce Type: cross Abstract: An open, networked web will allow agents to run frozen models from multiple vendors, keep their history private, and teach each other which tool to ca

Unthrottling the Tanh Jacobian in SAC: A Negative Result on Bang-Bang Control and MetaDrive

arXiv:2609.09478v1 Announce Type: new Abstract: Soft Actor-Critic (SAC) represents a continuous policy as an unbounded Gaussian that is squashed by tanh. The Jacobian of that map is partial a/partial

Vague2Detect: Handling Ambiguous Prompts in Knowledge-Based Open-World Detection

arXiv:2609.09949v1 Announce Type: cross Abstract: Real-world detectors must often interpret functional or ambiguous prompts, yet conventional models such as YOLO remain restricted to fixed class lists

VANTAGE-Bench: Evaluating the Infrastructure AI Gap in Vision-Language Models

arXiv:2609.09396v1 Announce Type: new Abstract: As Vision-Language Models (VLMs) advance toward physical deployment, the focus has remained on action-oriented Embodied AI evaluated on subject-centric

VFNet: Multi-View Spatio-Temporal Model for Void Fraction Estimation in Gas-Liquid Two-Phase Flow

arXiv:2609.09711v1 Announce Type: new Abstract: Void fraction, which quantifies the proportion of the fluid flow volume occupied by the gas phase, is a key parameter in the characterization of gas-liq

ViBe: Visual Behavior Adaptation for Perceptive Humanoid Whole-Body Control

arXiv:2609.09918v1 Announce Type: new Abstract: Motion tracking provides a scalable recipe for humanoid whole-body control. By design, the resulting trackers lack exteroceptive feedback hence reacting

Vision-language models know more about agriculture than they show and rubric-grounded verifications close the gap

arXiv:2609.09417v1 Announce Type: new Abstract: Vision-language models (VLMs) show promise for agricultural classification, but zero-shot performance on disease, pest, damage, quality, and species ide

VST: Verifiable Structured Transport for Auditable Agent-to-Agent Alpha Discovery

arXiv:2609.07065v1 Announce Type: new Abstract: Agent-to-agent (A2A) alpha discovery is slowed by repeated feedback cycles between mining and evaluation agents, whose hand-offs, in contemporary LLM mu

We're Cooked! - Probing LLM Political Alignment Via Conflict-Framed Recipe Translation

arXiv:2609.07568v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed for translation tasks, yet their implicit political positioning in such contexts remains unders

We're publishing our most detailed threat intelligence report to date. It covers how people tried to misuse Claude—for cyberattacks, influen…

model-releaseskarpathy--x

We're publishing our most detailed threat intelligence report to date. It covers how people tried to misuse Claude—for cyberattacks, influence operations, surveillance, biology, and building weapons—a

What Does an LLM-Agent Leaderboard Rank Actually Compare?

arXiv:2609.07785v1 Announce Type: new Abstract: An LLM-agent leaderboard invites a familiar inference: an agent ranked above another is the better agent. Public evaluation logs may not support that co

What Does MMLU Actually Measure? A Psychometric Audit of Difficulty Structure in Aggregate Benchmark Scores

arXiv:2609.09372v1 Announce Type: cross Abstract: Although MMLU is widely adopted as a benchmark for calibrating general AI capabilities, we psychometrically demonstrate that its aggregate score prima

What Eviction Destroys: A Restore-Counterfactual Audit of Forgetting in Agent Memory

arXiv:2609.08279v1 Announce Type: cross Abstract: Agent memory systems must discard stored information when their history exceeds a fixed token budget. Existing budget-accuracy frontiers quantify the

What LLM Trading Agents Actually Do in Production: A Six-Month, Population-Scale Record from Two Fleets

arXiv:2609.05663v1 Announce Type: new Abstract: We present a continuous, population-scale measurement record of autonomous language-model trading agents operating in production across two systems with

What Symmetry Buys a Learned Motion Planner

arXiv:2609.10033v1 Announce Type: new Abstract: Learning-based motion planners pay at training what classical planners pay per query. Trained in world coordinates, they relearn the same motion at ever

What to run at 128GB VRAM?

model-releasesr-localllama

Long time lurker, but I'm finally upgrading to 128GB VRAM, and I'm trying to figure out what to run. I had been leaning towards Qwen3.8 Flash-Next at ~Q4, and I generally prefer to not run anything be

When Agent Governance Helps

arXiv:2609.05531v1 Announce Type: cross Abstract: No specification says how a governed autotelic AI agent organization, where agents pursue self-generated goals inside guardrails, should be designed a

When and Why LLM Causal Priors Help: Closed-Loop Prior Selection for Amortized Causal Inference

arXiv:2609.06941v1 Announce Type: new Abstract: Causal effect estimation asks how an outcome would change under an intervention, and medicine, economics, and public policy all treat it as a foundation

When Auditors Fabricate: Batch-Size Degradation and Confident Hallucination in LLM Detection of Planted Document Contamination

arXiv:2609.09696v1 Announce Type: new Abstract: Large language models are increasingly proposed as automated auditors of document quality, yet their reliability as detectors of planted errors is poorl

When Does Defendant Statement Matter? A Study of Bias and Persuasion in LLM-Simulated Jurors

arXiv:2609.09887v1 Announce Type: new Abstract: LLMs have been used to simulate human decision-making in professional settings, yet their behaviors in common-law jury trials remain unexplored. We stud

When Does Memory Help? A Cost-Aware Evaluation of Long-Term Memory in Tool-Using LLM Agents

arXiv:2609.05441v1 Announce Type: new Abstract: Long-term memory for LLM agents is evaluated today by conversational recall benchmarks (LoCoMo, LongMemEval), which measure question answering over dial

When Intelligence Becomes Agency: A Theory of Governed, Proactive Agency for Symbiotic AI Systems

arXiv:2609.07741v1 Announce Type: new Abstract: Persistent AI assistants are intended to extend human attention, memory, and coordination across changing digital and physical environments. To be truly

Why Is Video Still So Expensive? A Survey of Inference-Efficiency Mechanisms in Video and Audiovisual LLMs

arXiv:2609.10355v1 Announce Type: cross Abstract: Video understanding has rapidly evolved toward video large language models (VideoLLMs): systems that couple video representations with pretrained larg

XAI-SDN: An Explainable Entropy-Guided Machine Learning Framework for Real-Time DDoS Detection in Software Defined Networks

arXiv:2609.05701v1 Announce Type: cross Abstract: One of the biggest risks faced by Software Defined Networks (SDN) is the Distributed Denial of Service (DDoS) attack in which a compromised controller

xDailyBench: Benchmarking LLMs on Professional Consultation for Real-Life Problems

arXiv:2609.07784v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for everyday assistance, yet existing benchmarks only partially reflect the requests users naturally

XYBench: Can LLMs Respond Pragmatically to Queries with Misconceptions?

arXiv:2609.06842v1 Announce Type: cross Abstract: When non-expert users ask LLMs for assistance, their queries can often have misconceptions (e.g., 'How do I parse XML with regex?'). In such cases, of

YallaMorph: A Benchmark for Evaluating Arabic Morphological Generation in Large Language Models

arXiv:2609.10153v1 Announce Type: new Abstract: Arabic morphology remains challenging for large language models, since fluent generation does not guarantee accurate morphosyntactic control. Existing A

You can also create editable financial models, research notes, and pitchbooks using your firm's own Excel, Word, and PowerPoint templates.

OpenAI now supports generating fully editable financial models, research notes, and pitchbooks directly in a firm’s existing Microsoft Office templates (Excel, Word, PowerPoint). Documents are created

model-releasesopenai--x

Zero-Shot Temporal Localisation of Audio Deepfakes in Multi-Speaker Conversations

arXiv:2609.10051v1 Announce Type: cross Abstract: Voice-cloning fraud increasingly relies on surgical injection: a genuine conversation in which only one or two sentences are replaced by synthetic spe

1-bit 27B in the browser: 25–30 tok/s on a 6 GB RTX 3060 Laptop (WebGPU, no install)

model-releasesr-localllama

mentria.ai is a browser inference engine I've been building solo, from scratch in WebGPU/WGSL. This week it crossed a milestone I had been chasing for a while: a 27B one-bit model answering at up to 3

3DHarnessBench: Probing Agentic 3D-to-Code Capabilities of Frontier Vision-Language Models

arXiv:2609.06535v1 Announce Type: new Abstract: We introduce 3DHarnessBench, a benchmark that evaluates the agentic ability of frontier vision-language models (VLMs) to recover 3D geometry as Blender

3DWay: Generalizing Robot Manipulation via 3D Consistent Waypoints

arXiv:2609.08224v1 Announce Type: new Abstract: Intermediate representations are key to bridging the modality gap between generalizable manipulation policies and large-scale pretrained vision-language

A dictionary learning framework for graphs via filters and optimal transport

arXiv:2609.05919v1 Announce Type: new Abstract: We propose a graph dictionary learning (GDL) framework where each graph is represented as a zero-mean Gaussian distribution derived from its filtered La

A language model walks into a benchmark. Scores 99.9% on MMLU. Wins a gold medal at the IMO. Solves SWE-bench. Passes Humanity’s Last Exam. …

model-releasescristobal-valenzuela--x

A language model walks into a benchmark. Scores 99.9% on MMLU. Wins a gold medal at the IMO. Solves SWE-bench. Passes Humanity’s Last Exam. Resists every jailbreak from Pliny the Liberator. The first

A Machine Learning Framework for Predicting Restaurant Food Waste to Support Sustainable Food Management

arXiv:2609.08078v1 Announce Type: new Abstract: Food waste in the restaurant sector poses a substantial challenge to environmental sustainability and economic efficiency. This paper presents an explor

A Measurement Study of LLM Inference Trade-offs Across Edge Continuum Hardware

arXiv:2609.08307v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as backends for intelligent web services, but serving them across the edge continuum requires balan

A Multimodal Label Forecasting Method for Aperiodic Visuo-Motor Time Series

arXiv:2609.07930v1 Announce Type: new Abstract: Deep learning models have been increasingly applied to Time Series Forecasting (TSF) in recent years. Transformer-based and MLP-based models have both b

A Statistical and Machine Learning Framework for Quantifying Offensive Impact in Professional Box Lacrosse

arXiv:2609.06610v1 Announce Type: new Abstract: Professional box-lacrosse statistics summarize outcomes but provide limited information about shot quality or the roles behind scoring opportunities. Th

AAMBERS-UAV: Acquisition-Aware Multimodal Backbone Evaluation and Ranking for UAV Weedy Rice Segmentation

arXiv:2609.05762v1 Announce Type: new Abstract: UAV image collections contain spatially and temporally related frames, yet semantic-segmentation benchmarks commonly split them at image level. Such spl

Accuracy is Not Enough: A Divergence-Based Approach to Evaluate Fidelity Loss in Quantized LLMs

arXiv:2609.07664v1 Announce Type: new Abstract: Deployment of Large Language Models (LLMs) on memory-constrained edge devices relies heavily on aggressive post-training quantization. However, evaluati

ACE: Adapter Consolidation across Experts for Parameter-Efficient Fine-Tuning of MoE LLMs

arXiv:2609.06072v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) of mixture-of-experts (MoE) models commonly attaches a separate low-rank adapter to each expert. This expert-wise

Activation- and Influence-Aware Ranks (AIR): Function-Preserving SVD Compression for LLMs

arXiv:2606.19993v2 Announce Type: replace Abstract: We present Activation- and Influence-Aware Ranks (AIR), an SVD-based LLM compression framework that guides each weight matrix's low-rank approximati

Adapting Neural Robot Dynamics on the Fly for Predictive Control

arXiv:2604.04039v2 Announce Type: replace Abstract: Accurate dynamics models are critical for the design of predictive controllers for autonomous mobile robots. Physics-based models are often too simp