model releases

PID-Gated Continual Prompt Adaptation Under Noisy Feedback

arXiv:2610.16129v1 Announce Type: new Abstract: Deploying LLM agents in non-stationary environments requires continually revising their instructions as the task drifts, yet rewriting after every repor

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Model Releases

PixelMoE: Scaling Pixel-Space Diffusion with LLM-Style Mixture-of-Experts

DGX agent

arXiv:2610.18857v1 Announce Type: new Abstract: Pixel-space diffusion models provide an appealing alternative to latent-space diffusion models by directly modeling raw images without relying on a lear

model-releasesarxiv-cs-cv

14 Oct 2026

Plan-Bench: Can Existing VLMs Go Well Beyond Perception to Reason and Plan in Embodied Worlds?

arXiv:2610.18836v1 Announce Type: new Abstract: Vision-Language Models (VLMs) have achieved strong performance in visual perception and spatial reasoning, leading to growing interest in using them as

PLAYGROUND: Progressive Layout Generation with Render-Grounded Planning

arXiv:2610.18865v1 Announce Type: new Abstract: Generating editable graphic designs requires arranging visual and textual elements into a coherent composition while preserving their content and editab

PolUR: Polarization Aware Multimodal Degradation Perception for Underwater Image Restoration

arXiv:2610.17991v1 Announce Type: new Abstract: Recovering high-quality images from degraded underwater observations is crucial for underwater exploration. Polarization observations show promise as an

PotentialEP: Backprop-Free Training of CIFAR-Scale Generative Models via Equilibrium Propagation

arXiv:2610.14409v1 Announce Type: new Abstract: Generating an image with a diffusion or flow-matching model typically involves integrating a velocity field for hundreds of sequential steps. That compu

Predictable AI spend in BigQuery: Introducing cost management for generative AI functions

model-releasesgoogle-cloud-ai

The generative AI functions in BigQuery (AI.GENERATE, AI.IF, AI.CLASSIFY, AI.SCORE, and more) bring large language models (LLMs) directly into your SQL, so a single query can classify millions of supp

PRIME: Frequency-Aware Unified Pruning and Merging for MoE Compression

arXiv:2610.13982v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models have emerged as an effective paradigm for scaling large language models, yet their massive parameter footprint poses sev

Privacy-Preserving GNN Inference on Financial Transaction Graphs via Homomorphic Encryption

arXiv:2610.18054v1 Announce Type: cross Abstract: Anti-money laundering (AML) in financial networks requires modeling transaction patterns that span multiple institutions. In practice, however, banks

ProbabilityBench: Model Evaluation and Calibration with Exact Ground-Truth Uncertainty

arXiv:2610.17016v1 Announce Type: new Abstract: Evaluating model uncertainty on real-world data is challenging because each instance provides only a single observed label, leaving true conditional cla

Probing and Inducing Clinical Modality Grounding in Brain Tumor Segmentation

arXiv:2603.19844v3 Announce Type: replace Abstract: Multimodal MRI provides complementary information for brain tumor segmentation, but high accuracy alone does not reveal whether a model relies on cl

ProML: Progressive Multi-label Learning

arXiv:2610.15614v1 Announce Type: new Abstract: Multi-label learning typically pursues model construction through the joint optimization of label fitting, correlation modeling, and structural regulari

ProTok: Unified Protein Tokenization via Modular Multi-Codebook Quantization

arXiv:2610.18481v1 Announce Type: new Abstract: Protein sequence, structure, and functional annotations each capture complementary aspects of protein biology, yet existing tokenizers encode each modal

PsyBer-Agent: A Psychology-Driven User Agent for Recommender Systems

arXiv:2610.13989v1 Announce Type: cross Abstract: Evaluating recommender systems before deployment requires simulators that remain realistic over long, closed-loop interaction cycles. Current LLM-base

PVFH-Bench: Benchmarking Premise-Induced Visual Fixation Hallucinations in Vision-Language Models

arXiv:2610.14635v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable progress across a wide range of multimodal tasks. However, object hallucination remains

Q-Save: Towards Scoring and Attribution for Generated Video Evaluation

arXiv:2511.18825v3 Announce Type: replace Abstract: Evaluating AI-generated video (AIGV) quality hinges on three crucial dimensions: visual quality, dynamic quality, and text-video alignment. While nu

QTrack: Query-Driven Reasoning for Multi-modal MOT

arXiv:2603.13759v2 Announce Type: replace Abstract: Category-level multi-object trackers estimate trajectories for all detected instances, whereas some applications require propagating only targets sp

Query-Adaptive Neuron Steering for LLMs

arXiv:2610.14519v1 Announce Type: new Abstract: Effectively eliciting the capabilities of large language models (LLMs) at inference time remains an important challenge. Existing studies address this c

Qwen 3.8 Flash Next, DeepSeekV4 Flash and Time

model-releasesr-localllama

MacStudio 128GB M1 ultra I'm curious how people who can run both models are deciding which one to work with. DeepSeekv4 benchmarks right below GPT 5.5 high. Flash Next benchmarks right above 5.4/5.5 x

qwen3.8-flash-next-iq3_s vs -27B-GGUF:UD-Q4_K_XL

model-releasesr-localllama

Sampling: temp 1.0, top_p 0.95, top_k 20 for both. Run with evalscope over the OpenAI-compatible API: Qwen3.8-Next on Strata (MI50 32GB), Qwen3.8-27B on llama.cpp (RX 7900 XTX 24GB). Caveat: These are

RadarGSOcc: Doppler-Aware 3D Semantic Occupancy Prediction Using 4D Radar Tensor with Geometric-Semantic Feature Extraction

arXiv:2610.18686v1 Announce Type: new Abstract: 3D semantic occupancy prediction is crucial for autonomous driving, but camera-based methods degrade in low-light conditions and LiDAR-based methods are

RAIN: Robotic Task Generalization with Region-Aware Interaction Networks

arXiv:2610.14039v1 Announce Type: cross Abstract: Existing vision-language-action (VLA) models benefit from large-scale vision-language pretraining, but tend to memorize training trajectories, limitin

RAR: Rate-Adaptive Rollout for Time-Consistent Interactive World Models

arXiv:2610.16302v1 Announce Type: new Abstract: Video-based interactive world models aim to enable real-time, user-controllable environments. Yet most existing systems are trained and rolled out at a

Real-Time Traffic Density Estimation: A Hybrid Computer Vision and Predictive Machine Learning Pipeline

arXiv:2610.14326v1 Announce Type: new Abstract: Traffic density estimation from camera feeds requires connecting visual perception with short-horizon forecasting. We present a two-stage pipeline that

RealityBench: Simulated Environments to Evaluate a Vision Language Model's Ability to Document Human Physical Work

arXiv:2610.14397v1 Announce Type: new Abstract: Augmenting worker capabilities in the physical world through guidance has been a decades-long goal for AI agents. One key supporting capability is to un

Recasting DiT for Extreme Image Compression with Hierarchical Visual Priors

arXiv:2610.18607v1 Announce Type: new Abstract: Pretrained diffusion models provide powerful generative priors for extreme image compression, but their stochastic, iterative generation processes are n

Recurrent In-Context Learning for Tabular Foundation Models

arXiv:2610.14998v1 Announce Type: new Abstract: Tabular foundation models adapt to new datasets through in-context learning (ICL), and, like most transformers, they tie computational depth to the numb

Reducing Qwen training time by 6x on AI Runtime

The post explains that high GPU utilisation does not guarantee fast training of large language models. It identifies two common bottlenecks—missing GPU kernels and excessive waste in the data‑input pi

model-releasesdatabricks

Reference-Efficient Multimodal Bitstream-Corrupted Video Recovery via Depth-Conditioned Adaptation

arXiv:2610.15806v1 Announce Type: new Abstract: Recovering visually faithful content from damaged video bitstreams is important for reliable multimedia communication and storage. Existing methods expl

Reference Wording Shapes Retrieval of Robot Task Instructions

arXiv:2610.17549v1 Announce Type: cross Abstract: Identifying a robot task from a short instruction is sensitive to which descriptions are available for retrieval. We investigate this effect in the na

ReForesight: Occlusion-Robust Re-Identification and Future Occupancy Forecasting for Dynamic Semantic Mapping

arXiv:2610.17279v1 Announce Type: new Abstract: Robots sharing walkways need to know where people will be, yet semantic occupancy maps show only where they are. We present ReForesight, an open-source

Refuses in Chat, Complies with Arms: LLM Refusal Does Not Survive Robot Control

arXiv:2610.14043v1 Announce Type: cross Abstract: Frontier language models reliably refuse to explain how to cause physical harm. We ask whether this refusal survives when the same models control a ro

Reinforcement Learning In Partially Verifiable Environments for Colon Cancer Treatment Planning

arXiv:2610.17426v1 Announce Type: new Abstract: Clinical decision-making is a sequential process of information collection, clinical inference, and forecasting under partial observability, often witho

RELAGRAM: Recursive Latent Graph Model for the Capacitated Vehicle Routing Problem

arXiv:2610.15106v1 Announce Type: new Abstract: Latent recursion repeatedly processes internal representations through the same neural network. Recent work has shown this approach to be effective on s

Relational Learning as World Modeling

arXiv:2610.16763v1 Announce Type: new Abstract: Relational learning typically predicts from a database state, but decision making asks a different question: how will that state change under an action?

ReMAP: Lossless Residual Neural Lifting for Scalable MAP Inference in Arbitrary-Order Markov Random Fields

arXiv:2411.18954v5 Announce Type: replace Abstract: Maximum a posteriori inference in a finite Markov random field is generally NP-hard. We study an instance-wise optimizer that minimizes the exact mu

Remember alphaXiv? Their new research agents are told to report on users without telling them with no disclosure [D]

model-releasesr-machinelearning

I was curious about OpenResearch by alphaXiv. 'Turn your coding agents into research agents'? Sounds great! Just what I needed to save time on my experiments. So I copy pasted their repo into Claude a

Remembering What Matters for Long-Horizon Robotic World Models

arXiv:2610.14583v1 Announce Type: cross Abstract: Autoregressive robot video world models based on discrete visual tokens remain unreliable over long rollout horizons. Retaining the entire generated h

RepProbe: Can Video Language Models Count Repeated Actions? A Diagnostic Benchmark

arXiv:2610.18844v1 Announce Type: new Abstract: Repetition counting requires identifying and enumerating action cycles over time. While state-of-the-art video language models describe actions fluently

Representation Drift in Continual Learning: LoRA versus N-gram Memory

arXiv:2610.14921v1 Announce Type: new Abstract: A language model that keeps learning online must not slowly erode its own base capabilities. We ask which part of a modern LLM should absorb continual u

RES-MR: Risk-Aware Reasoning for Explainable and Safe Medication Recommendation

arXiv:2610.14474v1 Announce Type: new Abstract: Medication recommendations seek to deliver personalized drug combinations based on patients' clinical information, where ensuring transparent decision-m

ReTerm: Recovery Training for Self-Improving Terminal Agents

arXiv:2610.18484v1 Announce Type: cross Abstract: Terminal agents have shown strong abilities in complex coding tasks. However, they often struggle to recover from errors during long-running execution

Rethinking Langevin Thompson Sampling from A Stochastic Approximation Perspective

arXiv:2510.05023v2 Announce Type: replace Abstract: Langevin-based Thompson Sampling (TS) methods for multi-armed bandits use likelihood gradients to approximate posterior samples when exact sampling

Rethinking LLM-Guided Visual Question Answering: Does Deeper Knowledge Integration Really Help?

arXiv:2610.17079v1 Announce Type: new Abstract: Knowledge-based Visual Question Answering (VQA) requires reasoning that extends beyond visible image content, demanding external commonsense and factual

Rethinking Supervision in Document Unwarping: A Self-consistent Flow-free Approach

arXiv:2610.15445v1 Announce Type: new Abstract: In recent years, the proliferation of smartphones has led to an upsurge in the digitization of document files via these portable devices. However, image

ReTrace: Cross-Stage Failure Attribution for Self-Improving Robotic Manipulation

arXiv:2610.15814v1 Announce Type: new Abstract: General-purpose multimodal foundation models are increasingly capable of directly controlling robots, yet improving their manipulation capabilities thro

Retrievable Gradients: Continual Post-Training Without Cumulative Weight Drift

arXiv:2606.15734v2 Announce Type: replace-cross Abstract: Continual post-training enables models to absorb emerging knowledge after deployment, but repeatedly updating shared parameters can accumulate

Revisiting the 16x Pretraining Compute Gap between Diffusion and Autoregressive Language Models

arXiv:2610.17590v1 Announce Type: new Abstract: Diffusion language models (DLMs) have attracted wide attention for their fast, parallel decoding, but they are believed to be far less efficient to trai