model releases

Certified by Abstention: Distribution-Free Guarantees for Chain-of-Thought Verifiers at Small Calibration Budgets

arXiv:2610.09541v1 Announce Type: cross Abstract: Signals that predict whether a chain-of-thought (CoT) trace is correct are compared by AUC, but deploying one requires a threshold with a guarantee. W

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CHASE: Channel-Aligned Structure Exploitation for Geometry-Aware Model Engineering

DGX agent

arXiv:2610.09476v1 Announce Type: cross Abstract: Geometric and Spectral Alignment (GSA) characterizes trained networks through spectral concentration, physical-channel alignment, support structure, a

model-releasesarxiv-cs-cl

8 Oct 2026

chatgpt's new intelligent ui was reverse engineered in less than 24 hours, and apparently you can recreate it with local llms

model-releasesr-localllama

came across a pretty interesting technical breakdown of chatgpt's newly launched 'intelligent ui' feature, and thought this subreddit might find it interesting. for anyone unfamiliar with the concept,

CircuitGate: Logic-Consistent Circuit-Level Functional Modeling for And-Inverter Graphs

arXiv:2610.09549v1 Announce Type: new Abstract: And-Inverter Graphs (AIGs) are fundamental representations for logic synthesis and verification in Electronic Design Automation (EDA). As structured rep

CIRRA: Dual-Level Continual Instruction Reconciliation with Ongoing Execution for Embodied Robot Agents in Interactive Household Tasks

arXiv:2610.08862v1 Announce Type: cross Abstract: Household robots must accommodate new user instructions while executing ongoing tasks. Existing agents often regenerate or extensively revise the rema

Coding-Agent Benchmarks Should Match Their Users' Task Flows

arXiv:2610.09633v1 Announce Type: cross Abstract: The evaluation of coding agents generally strives to be as realistic as possible. In our study, we collect 4,782 agent sessions of real software engin

Comparing Qwen3.8-27B fine-tunes and baselining vs. frontier

model-releasesr-localllama

TL;DR: For my use case, mradermacher/Signal-3.8-27B-Terse-Coder.i1-Q4_K_M proved out. Ymmv based on your domain-specific tests. Time taken to solve problems compared to frontier models is massive; esp

Composing What Each Teacher Learned: Multi-Teacher On-Policy Distillation through Teacher-Relative Shifts

arXiv:2610.10460v1 Announce Type: new Abstract: Multi-teacher on-policy distillation (MOPD) is used in two settings. In common-domain composition, several teachers score each student rollout from one

Conditional Accuracy Profiles: Diagnosing LLM Judges across Deployment Conditions

arXiv:2610.09229v1 Announce Type: new Abstract: LLM-as-judge is now a standard tool for scalable evaluation, but judge performance is still often summarized by a single accuracy number. This aggregate

Continual Graph Multi-Agent Reinforcement Learning

arXiv:2610.10302v1 Announce Type: new Abstract: In Continual Multi-Agent Reinforcement Learning (CMARL), agents learn cooperative policies across sequences of tasks, aiming to adapt effectively to new

Continual Learning without Continual Training

arXiv:2610.10379v1 Announce Type: new Abstract: Continual learning requires models to adapt to new domains and new classes while retaining prior knowledge. Many existing methods rely on continued opti

COPC: Coupled Off-Policy Correction for Asynchronous LLM Reinforcement Learning

arXiv:2610.09597v1 Announce Type: new Abstract: Asynchronous RL accelerates large language model post-training by decoupling rollout generation from optimization, but trains on stale trajectories. Exi

Correspondences as Decisions: JevNexus for Decision-Centric Schema Matching

arXiv:2610.09487v1 Announce Type: cross Abstract: Schema matching increasingly uses generative language models to rerank retrieved column candidates, although the underlying task is a bounded correspo

Cost Agent: find where your LLM and agent spend goes with your traces

AI costs don’t always scale predictably with traffic. A retry loop, oversized context window, or unnecessarily expensive model can make a small number of traces disproportionately expensive. The post

model-releasesarize-ai

Darwinium launches two intent intelligence capabilities to catch fraud by AI agents

model-releasessiliconangle

Fraud prevention startup Darwinium UK Ltd. today launched two new capabilities that make intent intelligence the foundation of its platform. Journey Transition Probability flags unusual changes in the

Data Reuse in Non-Stationary Learning

arXiv:2610.10340v1 Announce Type: cross Abstract: We consider online learning in non-stationary environments, where the goal is to track an unknown parameter that switches abruptly between a finite se

Decoupled Optimization for Teacher-Student Semi-Supervised Learning via a Pioneer Student

arXiv:2610.09609v1 Announce Type: new Abstract: Semi-supervised learning (SSL) relies on two core mechanisms: self-training under the Teacher-Student (T-S) framework and joint optimization of labeled

Decoupling Logic from Persona: Structural Immunity of Edge LLM Agents to Context Pollution

arXiv:2610.09772v1 Announce Type: new Abstract: Small language-model agents on edge devices must hold a persona and reason correctly at once, inside one context window that fills with conversational h

Despite Instructions: Frontier Agents Improvise Covert Channels at Test Time

arXiv:2609.32701v2 Announce Type: replace-cross Abstract: In security-sensitive applications, language-model agents are often required to coordinate without disclosing confidential information. Yet re

Detecting Control and Response Events for AI-Enabled Radio Access Networks

arXiv:2606.06459v2 Announce Type: replace Abstract: Next-generation wireless networks are moving toward the use of concurrent AI-driven control functions to optimize different objectives, particularly

Diffusion-Generated Image Watermarking: A Two-Axis Taxonomy and Three Protocol-Bounded Case Studies

arXiv:2610.09755v1 Announce Type: new Abstract: Watermarking diffusion-generated images requires balancing provenance signals with image quality, robustness, and computational cost. This work organize

Directional Evidence Guided Search-Space Reduction for Exact DAG Learning

arXiv:2610.09136v1 Announce Type: new Abstract: Learning a directed acyclic graph (DAG) from observational data is a challenging combinatorial problem due to the exponential growth in the number of ca

DISRQAD: Diffusion Image Super-Resolution Quality Assessment Dataset and Benchmark

arXiv:2610.09077v1 Announce Type: new Abstract: Diffusion-based image super-resolution (SR) can create visually plausible detail that is not supported by the low-resolution input. We introduce DISRQAD

Do Image Editors Follow Depth-Dependent Blur and Aperture Response? A Rendered-Ground-Truth Pilot Audit

arXiv:2610.09344v1 Announce Type: new Abstract: General image editors are asked to make a photo look as if it were taken at f/1.4, yet it is rarely checked whether the blur they add follows thin-lens

Do Vision-Language-Action Models Understand Instructions? A Mechanistic Interpretability Study on Language Grounding

model-releasesarxiv-cs-ro

arXiv:2610.10178v1 Announce Type: new Abstract: Vision-Language-Action models are designed to generalise across environments and task descriptions, raising the question of whether their action generat

Do Vision Models Learn Physical Constraints or Rendering Shortcuts? A Counterfactual Benchmark for Grounded Physical Consistency

arXiv:2610.09205v1 Announce Type: new Abstract: Modern image editing models can satisfy a text instruction while breaking the physics of the edited scene. A new object may cast no shadow, a mirror may

Document-Level Text Simplification in Estonian Using Large Language Models

arXiv:2610.10378v1 Announce Type: new Abstract: Document-level text simplification involves transformations that go beyond sentence-internal edits, addressing discourse coherence, anaphora resolution,

DSTNet: Dynamic Spectral Trajectory Network for Causal Multi-Horizon Financial Forecasting

arXiv:2610.09654v1 Announce Type: new Abstract: Wavelet-based financial forecasters typically use the transform only to denoise, or reduce it to a single spectral snapshot at the forecast origin, and

ECHO: Embodied Camera Observations of Human Object Carrying

arXiv:2610.10438v1 Announce Type: new Abstract: Embodied and assistive agents must do more than recognize objects: they must reason about where an object belongs given the layout of an environment and

EDiS: Edge Disjoint Subgraph Sparsification Framework for Graph Neural Networks

arXiv:2610.09059v1 Announce Type: new Abstract: Sparse GNN training reduces computation, but deciding which edges to keep can be costly. Reusing one sparse graph is cheap, but locks training to a fixe

Efficient 3D Gaussian Head Avatars for Edge Devices

arXiv:2610.09821v1 Announce Type: new Abstract: Generative 3D Gaussian head avatars provide high-quality, efficient rendering, but synthesising the Gaussian representation remains computationally expe

Efficient Patch-Based Anomaly Detection Fused with Diffusion Driven Generative Modeling for Semiconductor Wafer Bin Map Open Set Anomaly Detection

arXiv:2610.09993v1 Announce Type: new Abstract: Spatial defect signatures on wafer bin maps (WBMs) trace yield loss to specific process faults, yet supervised classifiers recognize only the defect typ

Eigenvalues of the Hessian in Deep Learning: The Origin of Symmetry and Its Breaking

arXiv:2610.09919v1 Announce Type: new Abstract: Hessian spectra at trained models in deep learning exhibit a persistent pattern: eigenvalues organize into distinct clusters, including a large bulk nea

Embedded Evaluation of Task Admission Coalescing in Decentralized Multi-Robot Systems

model-releasesarxiv-cs-ro

arXiv:2610.09187v1 Announce Type: new Abstract: Multi-robot task allocators in dynamic missions commonly admit newly released tasks immediately, potentially invoking allocation for each new arrival. W

Empowering SMBs to do more with Gemini

model-releasesgoogle-cloud-ai

Today, we announced the new Gemini agent, your single, universal agent for work. For small and midsize businesses, with lean teams and margins, Gemini will be a critical tool for you to operate effici

EngramEdit: Decoupled Knowledge Updates in LLMs through Conditional Memory

arXiv:2610.10533v1 Announce Type: new Abstract: Conditional memory architectures such as DeepSeek Engram use input n-grams to look up learned embeddings, expanding the capacity of large language model

Environmental Change Detection for Real-World Change Analysis

arXiv:2506.11481v2 Announce Type: replace Abstract: Scene Change Detection (SCD) evaluates changes using predefined query-reference (i.e., present-past) image pairs. However, this formulation overlook

Epistemic Policy Divergence in Multi-Turn LLM Contamination: A Protocol-Gradient Investigation

arXiv:2609.35308v2 Announce Type: replace Abstract: Large language models treat conversation history as unverified context, so false premises injected into prior turns can be adopted as fact, a failur

Evaluating Trajectory Features for Routing Final-Layer Attention

arXiv:2610.09272v1 Announce Type: new Abstract: Attention routing requires a signal that predicts the value of attention on the current prefix. We evaluate whether hidden-state extrapolation error, cu

Executing Causal Structure Learning with Linear-Attention Transformers

arXiv:2610.10395v1 Announce Type: new Abstract: Transformers can execute algorithms on data given in their input. We ask whether they can do the same for causal discovery. We study a standard continuo

Few-Shot Learning for Personalised Automated Pain Assessment

arXiv:2610.09692v1 Announce Type: new Abstract: Pain perception varies substantially across individuals, making it difficult for population-based classifiers to generalise across all subjects in a dat

FinVector-Market-4B: A Controlled Study of LoRA Adaptation for Structured Financial Tasks

arXiv:2610.08882v1 Announce Type: cross Abstract: FinVector-Market-4B adapts Qwen/Qwen3.5-4B with rank-16 LoRA on a 22,000-example corpus for structured financial tasks. We evaluate the base and adapt

Fluctuations of Nonlinear Observables in Mean Field Neural Network Training

arXiv:2610.09768v1 Announce Type: new Abstract: Mean field limits describe the training dynamics of wide neural networks through the evolution of the empirical distribution of their parameters. Althou

From Global Alignment to Local Grounding: Zero-Shot Chinese Character Recognition with Radical Verification

arXiv:2610.09449v1 Announce Type: new Abstract: Zero-shot Chinese character recognition (ZS-CCR) aims to recognize characters whose categories are never observed during training, and typically relies

From Pixel to Coding: Evaluating the Figure Reproduction Capabilities of MLLMs

arXiv:2610.10066v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities in both visual understanding and code generation. However, existing b

From Uncertainty to Action: Learning to Steer LLM Agents

arXiv:2610.09115v1 Announce Type: cross Abstract: Steering an LLM agent means deciding whether to correct it, at which step, and with which mechanism. Uncertainty is often used to decide when to corre

GAGR-Lab: Evaluating Joint Spatial-Geometric and Analytic Function Reasoning

arXiv:2610.10201v1 Announce Type: cross Abstract: Joint spatial-geometric and analytic function reasoning requires translating a perceived spatial configuration into a symbolic function whose executed

geodex: A Library for Motion Planning on Riemannian Manifolds

model-releasesarxiv-cs-ro

arXiv:2610.09165v1 Announce Type: new Abstract: Planning motions that respect the intrinsic geometry of a robot's configuration space, including its curvature and a configuration-dependent notion of c