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Large Language Models for Programming: Actually Fixing or Reimplementing Incorrect Code?

model-releasesarxiv-cs-cl

arXiv:2609.29410v1 Announce Type: new Abstract: Recent studies have shown that Large Language Models can effectively solve problems and fix bugs in diverse programming environments, including competit

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LastOPD: Taming Collapse in Latent On-Policy Distillation

DGX agent

arXiv:2609.28845v1 Announce Type: cross Abstract: On-policy distillation (OPD) corrects a student on the responses it writes, but its signal is the teacher's next-token distribution: it tells the stud

safetyarxiv-cs-cl

25 Sept 2026

LeafTrackNet: A Deep Learning Framework for Robust Leaf Tracking in Top-Down Plant Phenotyping

model-releasesarxiv-cs-cv

arXiv:2512.13130v2 Announce Type: replace Abstract: High-resolution phenotyping at the level of individual leaves offers fine-grained insights into plant development and stress responses. However, the

Leakage-Safe Machine Learning for Hydrogen Embrittlement Detection in 316L Stainless Steel: A Region-Held-Out Evaluation of Texture and Deep Features in SEM Micrographs

arXiv:2609.28567v1 Announce Type: new Abstract: Scanning electron microscopy (SEM) is routinely used to characterize the microstructural changes caused by hydrogen embrittlement (HE) in structural ste

local-aiarxiv-cs-lg

Applications

Learnable Time-Frequency Masks for Explaining Time-Series Classifiers

arXiv:2609.29270v1 Announce Type: new Abstract: Time-series explainability remains challenging because discriminative information is often encoded in latent frequency or time-frequency features rather

applicationsarxiv-cs-lg

Applications

Learned Cross-Task Relationships in Multi-Task Models

arXiv:2609.28776v1 Announce Type: new Abstract: We propose a framework that learns cross-task relationships in multi-task models by approximating the joint distribution of task labels through targeted

applicationsarxiv-cs-ai

Learning a Flow to Self-Supervised Representations

arXiv:2609.29350v1 Announce Type: new Abstract: Explicit geometric references offer a direct way to structure self-supervised representations. Existing adversarial distribution-matching formulations,

safetyarxiv-cs-cv

Learning and interpreting policies for simultaneous entanglement requests in quantum networks

model-releasesarxiv-cs-lg

arXiv:2609.30157v1 Announce Type: cross Abstract: Future quantum networks will make use of entanglement to perform numerous tasks, such as sending quantum information over long distances, distributed

Learning Better Reasoning for Generative Recommendation with Semantic IDs

arXiv:2609.29973v1 Announce Type: cross Abstract: Generative recommendation reformulates item retrieval as sequence generation, allowing a unified model to directly generate the next item from a user'

safetyarxiv-cs-ai

Learning Causal Structure of Time Series using Best Order Score Search

arXiv:2603.05370v2 Announce Type: replace-cross Abstract: Causal structure learning from observational data is central to many scientific and policy domains, but the time series setting common to many

safetyarxiv-cs-ai

Learning from Mixed-Quality Deployment Experience for Robot Manipulation

arXiv:2609.29000v1 Announce Type: new Abstract: Robot policies deployed in real environments naturally accumulate mixed-quality experience, including successful executions, partial progress, and failu

safetyarxiv-cs-lg

Tutorials

Learning New Words from Unlabeled Test Data in Automatic Speech Recognition

arXiv:2609.28877v1 Announce Type: cross Abstract: New words are invented every day. A human listener can learn a new word by hearing it clearly once and inferring its usage from sentence context. This

tutorialsarxiv-cs-cl

Learning to Discover Interesting Mathematics

arXiv:2609.28603v1 Announce Type: cross Abstract: Recently, Large Language Models (LLMs) have been increasingly able to solve advanced mathematical problems, including many that have been open for dec

researcharxiv-cs-ai

Learning to Ideate for Scientific Impact

arXiv:2609.29802v1 Announce Type: new Abstract: Scientific ideation is increasingly mediated by large language models, but current ideation systems are usually trained and evaluated on immediately jud

researcharxiv-cs-ai

Hardware

Less is More: Encoder-only Audio-Visual Segmentation

arXiv:2609.29121v1 Announce Type: cross Abstract: Audio-Visual Semantic Segmentation (AVSS) aims to identify, segment, and classify sound-emitting objects in video frames. Previous Transformer-based A

hardwarearxiv-cs-ai

Tutorials

Let Training Guide Selection: Online Synthetic Data Filtering via Real-Anchored Utility

arXiv:2609.29988v1 Announce Type: new Abstract: Synthetic data can scale training supervision when real-world data are limited, but noise and distribution mismatch can reduce its value. Existing synth

tutorialsarxiv-cs-lg

Lightweight Probabilistic Downscaling from a Deterministic Base Model

arXiv:2609.29383v1 Announce Type: new Abstract: Climate data downscaling is the task of increasing the spatial resolution of climate data, typically by generating fine-resolution regional climate data

Lightweight Vision Transformer-Based U-Net for Brain Tumor Segmentation from MRI

arXiv:2609.29785v1 Announce Type: new Abstract: Accurate brain tumor segmentation from Magnetic Resonance Imaging is essential for diagnosis, treatment planning, and surgical guidance. Although Convol

local-aiarxiv-cs-cv

Likelihood Ranking doesn't Scale Like Prompting in LLMs

arXiv:2609.29390v1 Announce Type: new Abstract: LLM evaluation is commonly performed either by prompting models to produce answers or by scoring candidate outputs with likelihood-based metrics. In mul

researcharxiv-cs-cl

Limited Structural Reliability in Public Educational Prediction Benchmarks: A Four-Dimension Audit of Seven Datasets

model-releasesarxiv-cs-lg

arXiv:2609.29625v1 Announce Type: new Abstract: Across seven public educational prediction datasets, three passed all four pre-modeling reliability checks; the remaining four either failed group-aware

LiveMathematicianBench: A Live Benchmark for Research-Level Mathematical Reasoning with Proof Sketches

model-releasesarxiv-cs-ai

arXiv:2604.01754v2 Announce Type: replace-cross Abstract: Mathematical reasoning is a hallmark of human intelligence, and whether large language models (LLMs) can meaningfully perform it remains a cen

LLM Agents Can Easily Tamper With Their Own Traces

model-releasesarxiv-cs-ai

arXiv:2609.30266v1 Announce Type: cross Abstract: Asynchronous monitoring, incident investigations, and compliance audits primarily rely on agent traces to reconstruct what happened. These analyses as

LLM Forensics: Where Do Backdoors Hide? Localizing and Controlling Trigger Mechanisms with Sparse Autoencoders

arXiv:2609.07746v2 Announce Type: replace Abstract: Even though backdoors in LLMs have been a growing concern, their inner workings are still under heavy scrutiny. Trigger-based backdoors are easy to

researcharxiv-cs-cl

LLM on a budget part 2, from P102-100 to CMP 50HX.

I finally got around to upgrade the GPU's. First a word of warning, when upgrading GPU's on P520 you have to be extra careful not to slot the card on any angle other than straight when installing or w

LLM surprisal is necessary but not sufficient to capture English garden-path effects: Evidence from joint latent modeling of reading paradigms

arXiv:2602.04489v2 Announce Type: replace Abstract: Temporarily ambiguous garden-path sentences ('While the team trained the striker wondered... ') are known to cause processing difficulty, which can

researcharxiv-cs-cl

LLMersion: A Local-First AI Agent Framework for Low-Cost Home Language Learning toward Educational Equity

model-releasesarxiv-cs-cl

arXiv:2609.29672v1 Announce Type: new Abstract: Artificial intelligence helps education most where an essential provision has been rationed by cost. For language learners that provision is a teacher's

Long-Tail Adaptive Flow Matching with Explicit Conditional Consistency Guidance for Precise Multimodal Face Synthesis

arXiv:2609.29581v1 Announce Type: new Abstract: Although diffusion-based methods have substantially improved the controllability of multimodal face synthesis, their semantic alignment remains suboptim

safetyarxiv-cs-cv

Looks the Same, Answers Differently: Flip-Direction Steering for Robust Vision-Language Reasoning

model-releasesarxiv-cs-cv

arXiv:2609.28851v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong visual reasoning performance, yet subtle changes from routine image capture and processing can alter their

Agents

Low-Cost Assays for Measuring Model Behavior Across Vendors and Releases

arXiv:2609.30012v1 Announce Type: cross Abstract: Language models advise people, keep them company, and write software while they sleep. Measuring what they do is hard: behavior has to be sampled repe

agentsarxiv-cs-ai

M-plicits: Neural Implicit Surfaces via Nested Multiscale Residuals

model-releasesarxiv-cs-cv

arXiv:2609.28684v1 Announce Type: new Abstract: Encoding input coordinates with sinusoidal functions into multi-layer perceptrons (MLPs) has proven effective for implicit neural representations (INRs)

M^2PFN: End-to-End Disentangled Alignment for Generalizable Multimodal In-Context Learning in Alzheimer's Disease

arXiv:2609.28836v1 Announce Type: cross Abstract: While various multimodal methods combining imaging and tabular data for Alzheimer's disease (AD) diagnosis were proposed, they are often limited in ge

safetyarxiv-cs-ai

Applications

M3GD: Multi-Modal Multi-View Geometric Diffusion for Camera--LiDAR Novel View Synthesis

arXiv:2609.30056v1 Announce Type: cross Abstract: Robotic novel view synthesis (NVS) must recover both visual appearance and metric 3D structure, yet most generative NVS methods rely only on images, o

applicationsarxiv-cs-cv

M5 Ultra 80Core GLM-5.3-Flash on DwarfStar Speeds

I've been playing around with various models on the M5 Ultra 256GB 80-core Mac Studio. These are the results over many rounds of agentic inferencing. I'm happy with the performance. Glad to have the l

local-air-localllama

Machine Unlearning for Gibbs Supervised Learning Algorithms

arXiv:2609.29409v1 Announce Type: cross Abstract: In this paper, a method for achieving exact unlearning for Gibbs supervised learning algorithms is proposed using a variational formulation inspired b

Make Volta Fast Again

For those who have V100 cards, I wanted to point you to 1Cat-vLLM, a vLLM fork that enables optimized serving for these cards. Showing stats for Qwen3.6-35b comparing a Strix Halo with a hughly optimi

Agents

Markerless Multi-Modal Autonomous Robotic Inspection of Large Space Structures

arXiv:2609.29644v1 Announce Type: new Abstract: Future orbital infrastructures, such as deployable antennas, solar farms, and large orbital platforms will require autonomous inspection systems able to

agentsarxiv-cs-ro

Hardware

Match4Annotate: Cross-Video Annotation Transfer in Ultrasound via Implicit Feature Flow-Guided Matching

arXiv:2603.06471v3 Announce Type: replace Abstract: Acquiring per-frame annotations for ultrasound videos is costly and requires clinical expertise, limiting learning-based analysis. We study cross-vi

hardwarearxiv-cs-cv

Matrix Aggregation Operators

arXiv:2609.28562v1 Announce Type: cross Abstract: Aggregation theory has traditionally focused on operators defined over vectors. However, many applications-including Multi-Criteria Decision Making, G

MDE-VIO: Enhancing Visual-Inertial Odometry Using Learned Depth Priors

arXiv:2602.11323v2 Announce Type: replace Abstract: Traditional monocular Visual-Inertial Odometry (VIO) systems struggle in low-texture environments where sparse visual features are insufficient for

researcharxiv-cs-cv

Med-AR: Autoregressive Vision-Language Pretraining for Long-Tailed Chest X-Ray Classification and Uncertainty-Aware Evaluation

arXiv:2609.29156v1 Announce Type: cross Abstract: Long-tailed chest X-ray classification requires visual representations that capture both common abnormalities and subtle, infrequent findings. We prop

researcharxiv-cs-ai

Meet Observer, an agent that uses local LLMs to monitor your screen, so you don't have to

Hey r/ollama ! I'm Roy, solo dev of Observer. Observer is a free open-source agent that uses small local LLMs to monitor your screen, so you don't have to. This is the demo of the agent that controls

local-air-ollama

MemGuard-Alpha: Limits of Membership Inference for Detecting and Filtering Memorization-Contaminated Signals in LLM-Based Financial Forecasting

arXiv:2603.26797v2 Announce Type: replace Abstract: Large language models are increasingly used to generate financial alpha signals, but many have memorized the historical data in their training corpo

MeshHeal: Two-Timescale Self-Healing for Gray Failures in Decentralized LLM Agent Networks

arXiv:2609.29015v1 Announce Type: new Abstract: Decentralized LLM-based multi-agent systems coordinate through local interactions, but an agent can remain responsive while its task-solving quality per

local-aiarxiv-cs-ai

MEVL-STP: Multi-Encoder and Vision Language Model for Arbitrarily Shaped Scene Text Spotting

arXiv:2609.28857v1 Announce Type: new Abstract: Scene text spotting remains challenging for arbitrarily shaped text instances such as curved signs and dense multi-oriented characters in natural images

local-aiarxiv-cs-cv

MF-SCBO : Multi-fidelity Scalable Constrained Bayesian Optimization

model-releasesarxiv-cs-lg

arXiv:2609.29941v1 Announce Type: new Abstract: Many real-world optimization problems rely on expensive simulations or experiments, making the efficient use of available data essential. Multi-fidelity

Mica v0.1 4B got an iron pickaxe in real Minecraft without generating a single token

Mica v0.1 4B playing a real Minecraft 1.20.4 server. Video attached. How it works - Each step the bot's live game state (inventory, nearby blocks, entities, last result) is written out as text. - Mica

Mica v0.1 4B: open Jev-style decision model (yes/no, choice, score) that runs on an 8 GB GPU — trained for under $30 of GPU time

I've been building a small decision model for agent loops: gates, routers, 'should I ask the user or just act' checks. It's out now as Mica v0.1 4B (Apache-2.0). What it does You give it a state, a qu

MILO: Efficient Many-shot In-Context Learning with Block-wise Low-rank Compression

arXiv:2609.29913v1 Announce Type: new Abstract: Many-shot in-context learning (ICL) enables large language models (LLMs) to adapt to complex tasks by conditioning on thousands of demonstration example

local-aiarxiv-cs-cl