Search: “models”

arXiv:2510.12899v3 Announce Type: replace Abstract: Recently, several multi-turn dialogue benchmarks have been proposed to evaluate the conversational abilities of large language models (LLMs). As LLM

applicationsarxiv-cs-cl

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Efficient Training with Foresight: Multi-Token Auxiliary Supervision for Autoregressive Image Generation

DGX agent

arXiv:2608.25386v1 Announce Type: new Abstract: Autoregressive (AR) image generation has shown strong potential for scalable high-fidelity synthesis by modeling images as discrete token sequences. How

researcharxiv-cs-cv

27 Aug 2026

EncoTESS: Age-Sensitive Encodings from Raw TESS Light Curves

arXiv:2608.25019v1 Announce Type: cross Abstract: Main sequence stars of spectral types late F through M exhibit systematic variability in photometric light curves, particularly when they are young. R

GraftSR: Grafting Authentic Textures for Real-World Image Super-Resolution via Identical-Instance Guidance

model-releasesarxiv-cs-cv

arXiv:2608.25334v1 Announce Type: new Abstract: Diffusion-based real-world image super-resolution (SR) achieves impressive perceptual quality but inherently suffers from severe texture hallucination.

If you maintain a skill library for long-horizon agents, this one is worth your time. (bookmark it) It discusses one of most common topics I…

If you maintain a skill library for long-horizon agents, this one is worth your time. (bookmark it) It discusses one of most common topics I get asked about these days. It shares some good ideas on ho

model-releasesdair-ai--x

InteractGesture: Progressive Chunk Guidance for Continuous Streaming Co-Speech Gesture Control

arXiv:2608.25734v1 Announce Type: new Abstract: Co-speech gesture generation has made significant progress toward realistic full-body motion from speaker audio, yet existing models lack fine-grained s

researcharxiv-cs-cv

Key Point Analysis Needs Structure Recovery: Task Definition, Dataset Diagnosis, and a Structure-Aware Benchmark

arXiv:2608.25854v1 Announce Type: new Abstract: Key Point Analysis (KPA) aims to identify a concise set of key points that summarize a collection of arguments together with their prevalence. We argue

Krea2 Turbo Distill 4 step LoRA (NOT a New Checkpoint... YET to share / still mid training) ... but fun 2-step extreme experiment with surprising results... (OUT OF TRAINING SPEC, which is 4 steps!)

model-releasesr-stablediffusion

I am sure for those of you who have been following my 4 step Krea 2 Turbo LoRA, you would know from my previous posts the work of progress I have been sharing with you ( if not see here - https://www.

LibriBrain100: One Hundred Hours of Broad and Deep MEG Data for Neural Speech Decoding at Scale

arXiv:2608.25204v1 Announce Type: cross Abstract: We introduce LibriBrain100, a large-scale MEG dataset for speech decoding designed from the ground up for reproducible, standardised evaluation. Libri

Local Ai

LLMTrace: A Corpus for Classification and Fine-Grained Localization of AI-Written Text

arXiv:2509.21269v2 Announce Type: replace Abstract: The widespread use of human-like text from Large Language Models (LLMs) necessitates the development of robust detection systems. However, progress

local-aiarxiv-cs-cl

Tutorials

Long-Term Behavioral Evaluation for Trusted Collaborator Selection via Bidirectional Mamba

arXiv:2608.25232v1 Announce Type: new Abstract: Effective selection of trustworthy collaborators is crucial to ensuring the successful completion of collaborative tasks, which requires accurate assess

tutorialsarxiv-cs-lg

Safety

Lower-Resource, Higher Scores: Language Bias in LLM Evaluators

arXiv:2607.14480v3 Announce Type: replace Abstract: LLM evaluators (trained reward models and prompted LLM-as-a-Judge) are routinely validated via pairwise accuracy. In a multilingual setting, this op

safetyarxiv-cs-cl

Memory-V2V: Memory-Augmented Video-to-Video Diffusion for Consistent Multi-Turn Editing

arXiv:2601.16296v3 Announce Type: replace Abstract: Video-to-video diffusion models achieve impressive single-turn editing performance, but practical editing workflows are inherently iterative. When e

researcharxiv-cs-cv

MMEmb-R1: Reasoning-Enhanced Multimodal Embedding with Pair-Aware Selection and Adaptive Control

arXiv:2604.06156v2 Announce Type: replace-cross Abstract: MLLMs have been successfully applied to multimodal embedding tasks, yet their generative reasoning capabilities remain underutilized. Directly

Non-Asymptotic Bounds for Closed-Loop Identification of Sub-Exponentially Growing Nonlinear Stochastic Systems

arXiv:2412.04157v2 Announce Type: replace-cross Abstract: We investigate the problem of least squares parameter estimation from single-trajectory data for discrete-time, unstable, closed-loop nonlinea

ONNX-Net: Towards Universal Representations and Instant Performance Prediction for Neural Architectures

arXiv:2510.04938v2 Announce Type: replace-cross Abstract: Neural architecture search (NAS) automates the design process of high-performing architectures, but remains bottlenecked by expensive performa

Tutorials

PaSta: Noisy Node Classification with Partial Label Learning

arXiv:2608.25365v1 Announce Type: new Abstract: Noisy node classification problem is a fundamental yet challenging task for real-world graph-related web services, where node labels are often corrupted

tutorialsarxiv-cs-lg

Plans You Can Check: Verifier-Grounded Learning of an Open-Weight Planner for Executable Video-Editing

arXiv:2608.25622v1 Announce Type: cross Abstract: Practical video editing is not only pixel generation: an editor must turn a brief, a clip pool, music metadata, and hard constraints into an executabl

PlanSightRAG: A Visual-First Multimodal RAG for Automating Question Answering and Compliance Checking for Civil Standard Plans

arXiv:2608.26091v1 Announce Type: cross Abstract: Civil infrastructure compliance checking has long relied on engineers manually reading legacy 2D plans; however, OCR-based automation strips away the

Safety

PreResQ-R1: Response-Preference Disentangled Ranking-and-Scoring Reinforcement Optimization for Robust Visual Quality Assessment

arXiv:2511.05393v2 Announce Type: replace Abstract: Visual Quality Assessment (QA) seeks to predict human perceptual judgments of visual fidelity. While recent multimodal large language models (MLLMs)

safetyarxiv-cs-cv

PRISM: Projection-Integrated Sampling-Based MPC with Bayesian Cost Tuning for Bimanual Manipulation

model-releasesarxiv-cs-ro

arXiv:2608.25666v1 Announce Type: new Abstract: Bimanual manipulation in cluttered, contact-rich environments remains challenging because it requires coordinated motion generation, interaction-aware p

Qwen3.8-Flash-Next: Time to Update Those Benchmarks

model-releasesr-localllama

specs hardware: M4 Max 128GB Studio inference engine: oMLX & lllama.cpp insights it still very early, so had to disable oMLX K/V caching, qwen4_exp architectureis not yet supported + the obvious n-gra

Tutorials

R^3: Training Robots to Reason in Natural Language via Reinforcement Learning

arXiv:2608.26053v1 Announce Type: cross Abstract: Reasoning in language allows foundation models to spend more test-time compute on hard problems, such as those requiring decomposition, constraint tra

tutorialsarxiv-cs-cl

Applications

Recurrent Neural Networks in Linguistic Theory: Revisiting Pinker and Prince (1988) and the Past Tense Debate

arXiv:1807.04783v3 Announce Type: replace Abstract: Can advances in NLP help advance cognitive modeling? We examine the role of artificial neural networks, the current state of the art in many common

applicationsarxiv-cs-cl

RefLAM: A Reference-Grounded Line Annotation Pipeline for Historical Arabic Manuscripts

arXiv:2608.25140v1 Announce Type: cross Abstract: Existing approaches to building line-level Arabic handwritten-text-recognition (HTR) training data either rely on fully manual annotation, which does

Safety

Retrieved But Not Reliable: A Survey on Attacks, and Defenses in Retrieval-Augmented Generation

arXiv:2608.24977v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enhances large language models by grounding outputs in external knowledge, improving factuality and reducing hall

safetyarxiv-cs-cl

Sample Margin-Aware Recalibration of Temperature Scaling

model-releasesarxiv-cs-cv

arXiv:2506.23492v2 Announce Type: replace-cross Abstract: Recent advances in deep learning have significantly improved predictive accuracy. However, modern neural networks remain systematically overco

Agents

Scalable Supervision for Software Agents via Patch Reasoning

arXiv:2510.22775v2 Announce Type: replace Abstract: While language model agents have advanced software engineering, existing test-based supervision is limiting its scalability on real-world issues. Th

agentsarxiv-cs-cl

StablePDENet: Enhancing Neural Operator Stability through Physics-Informed Residual-Sensitivity Regularization

arXiv:2601.06472v2 Announce Type: replace Abstract: Learning solution operators for differential equations with neural networks has shown great potential in scientific computing, but ensuring their st

Agents

TAU-Agent: An Agentic Retrieval-Augmented Framework for Traffic Anomaly Understanding

arXiv:2608.25935v1 Announce Type: new Abstract: Traffic Anomaly Understanding (TAU) requires models and systems to detect, reason about, and explain anomalous events in transportation videos. To addre

agentsarxiv-cs-cv

The Changing Geometry of Grammar: Dimensionality and Neighborhood Reorganization across Transformer Layers

arXiv:2608.25166v1 Announce Type: new Abstract: Transformer representations describe trajectories through high-dimensional vector spaces, which are shaped dynamically as tokens incorporate relational

Agents

TraceML: An Empirical Analysis of Human-Agent Planning in Machine Learning Development

arXiv:2608.26086v1 Announce Type: new Abstract: Large language models write correct code for isolated problems but remain far weaker at autonomous machine-learning development, where an agent must rev

agentsarxiv-cs-lg

Trust the Mass: Forced Weights in KV-Cache Eviction

arXiv:2608.25230v1 Announce Type: cross Abstract: Every deployed sparse-attention or KV-cache-eviction rule keeps a subset of the keys, discards the rest, and renormalizes the attention weights over t

Unfolding Scientific Papers into Multi-Turn Generation Trajectories for Continued Pre-Training

arXiv:2608.25826v1 Announce Type: new Abstract: A recent line of synthetic-data work reconstructs the thinking behind existing text rather than rewriting the text itself, but it operates on short web

When Personality Meets Quantization: A Layer-wise MBTI Analysis of Quantized LLMs

arXiv:2608.25977v1 Announce Type: new Abstract: Personality is increasingly important in large language models (LLMs), as it shapes users' trust, engagement, and emotional experiences. While the Myers

researcharxiv-cs-cl

When Should a Network Emit Geometry, and When Should It Detect It? Readout, Reconciliation, and Representation in Floorplan Vectorization

model-releasesarxiv-cs-cv

arXiv:2608.25608v1 Announce Type: new Abstract: A network trained to recover the walls, openings, and rooms of a rasterized floorplan can produce its output in two ways: by emitting the geometry as an

40 defensive security-audit skills distilled from Ox Alpha

Recently, I've been building a project where sandboxing and isolation of certain features was required. However, for the life of me, I couldn't ask Fable 5 a simple question without it accusing me of

model-releasesr-ollama

Adaptive Influence Graphs for Failure Attribution in Multi-Agent Systems

model-releasesarxiv-cs-ai

arXiv:2608.24361v1 Announce Type: new Abstract: Multi-agent LLM systems are increasingly deployed in real-world applications, where failures can be costly and difficult to localize. Despite growing ef

Adaptive prediction theory combining offline and online learning

arXiv:2512.00342v2 Announce Type: replace Abstract: Real-world intelligence systems usually operate by combining offline learning and online adaptation with highly correlated and non-stationary system

AI assistant Instinct is raising a 250M Series B co-led by Index Ventures and Benchmark at a 2.5B valuation, bringing its total raised to $350M (Kate Clark/Wall Street Journal)

Kate Clark / Wall Street Journal: AI assistant Instinct is raising a 250M Series B co-led by Index Ventures and Benchmark at a 2.5B valuation, bringing its total raised to 350M — Buzzy startup Instinc

model-releasestechmeme

Local Ai

ALPHABET: A Laplace-Pole History Aggregator with Banked Exponential Transport

arXiv:2608.24051v1 Announce Type: new Abstract: Can a sequence model remain competitive with only a few thousand parameters and an explicitly auditable prediction interface? We introduce ALPHABET, a c

local-aiarxiv-cs-lg

Anyone else doing eGPUs (OCuLink)?

model-releasesr-localllama

Upgraded to a 5070 Ti so I could run Qwen 3.8 27B, which works perfectly, but didn't want to let the old 4070 Ti go to waste. The cards would touch if I put them both in the PC and I knew the heat wou

Are Android GUI Agents Robust Against Runtime Anomalies? AnTrap: Evaluating Agents in Dynamic Adversarial Environments

model-releasesarxiv-cs-ai

arXiv:2608.24099v1 Announce Type: new Abstract: GUI agents often encounter dynamic anomalies when deployed on Android devices, from unexpected pop-ups to action misuse, yet existing benchmarks lack sy

Compared Qwen 3.8 27B community quants on RTX 6000 vs Claude Opus 4.6

model-releasesr-localllama

*part 2 of an earlier post: previous quant comparison with voxel island creation this time I rented three rtx pro 6000 96gb, on each one I launched a qwen 3.8 27b quant and gave them 4 identical promp

Coronavirus Optimization Algorithm: A Success-History Adaptive Evolutionary Framework with Archive-Assisted Search and Stagnation Recovery for Global Optimization

model-releasesarxiv-cs-ai

arXiv:2608.23847v1 Announce Type: cross Abstract: This paper proposes the Coronavirus Optimization Algorithm (COA), a SARS-CoV-2-inspired success-history adaptive evolutionary optimizer for box-constr

Data Predictability Shapes Weibull Weight-Scale Growth in Transformer Training

arXiv:2608.23573v1 Announce Type: new Abstract: A trained transformer's weight magnitudes can be summarized by a two-parameter Weibull distribution whose shape k approx 1.2 is stable across layers and

Deep Learning Super Resolution for Satellite Cloud Mask Downscaling

arXiv:2608.24715v1 Announce Type: cross Abstract: A vast amount of optical satellite data is being transmitted to Earth-based servers every day, and more than half of this data is affected by haze or

researcharxiv-cs-ai

DriftAD: Visually-Guided Text Drift for Few-Shot Industrial Anomaly Detection

arXiv:2608.23723v1 Announce Type: new Abstract: Few-shot anomaly detection (FSAD) has recently benefited from vision-language models such as CLIP, which enable anomaly de?tection by aligning visual fe

researcharxiv-cs-cv