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Interpretable Deepfake Detection in Videos via Explicit Forensic Features and Temporal Modeling

arXiv:2610.03380v1 Announce Type: new Abstract: Deepfake detection in videos remains challenging, as manipulated content may appear visually consistent at the frame level while exhibiting subtle tempo

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Model Releases

Introducing GLM 5.3 on Amazon Bedrock

DGX agent

GLM 5.3 from Z.ai is now available on Amazon Bedrock: a 753B-parameter mixture-of-experts model built for coding and long-horizon agentic tasks. Learn how to invoke it with the OpenAI-compatible APIs,

model-releasesaws-ml-blog

5 Oct 2026

Introducing Google Cloud Modernize, transforming for (and with) AI

model-releasesgoogle-cloud-ai

Today, we’re announcing Google Cloud Modernize, an end-to-end transformation portfolio to help enterprises collapse multi-year roadmaps with the power of AI. Google Cloud Modernize brings together Goo

Investigating the Role of Reasoning-Language Alignment in Monolingual Retrieval-Augmented Generation

arXiv:2610.03136v1 Announce Type: new Abstract: Reasoning traces improve large language models (LLMs), but current models are trained to reason mostly in English. It has been shown that forcing a mode

iS-KV: Online Low-Rank KV Cache Compression via Block-Incremental SVD

arXiv:2610.02815v1 Announce Type: new Abstract: Long chain-of-thought reasoning substantially increases KV-cache memory during autoregressive decoding, as every generated token introduces new key and

Keep the Effect, Drop the Actor: Programmable Effect-to-Execution World-Action Models

model-releasesarxiv-cs-ro

arXiv:2610.02398v1 Announce Type: new Abstract: A robot demonstration records two things in the same frames: what happened to the objects, and how one particular arm made it happen. We condition on th

Keeping JEPA World Models Plannable When Little of the Frame Moves

arXiv:2610.03137v1 Announce Type: new Abstract: Specifying a goal in language rather than as a goal frame is a natural interface for planning with a latent world model, but testing it needs scenes in

Kinematics-Induced Multimodal 3D Human Pose Estimation with Subject-Level Privacy

arXiv:2610.02943v1 Announce Type: new Abstract: Multimodal 3D Human Pose Estimation (3D HPE) combines complementary information from RGB, LiDAR, and mmWave radar, but models trained on correlated obse

k_llama.cpp MoE Optimizations: Expert Residency, Hybrid CPU/GPU Execution, Q2_0 Support

Finally finished my fork: https://github.com/IceFog72/ik_llama.cpp Nothing else I wanted to add/try currently works In short, it now has: Bandwidth-adaptive CPU/GPU execution Shared expert-residency i

Landscape-Dependent Performance of Photonic Quantum Solvers in QUBO Feature Selection for Financial Risk Detection

arXiv:2610.03161v1 Announce Type: cross Abstract: Feature selection for imbalanced classification tasks such as credit card fraud and consumer default detection requires balancing predictive relevance

Language Models that Play Chess and Explain Their Moves

arXiv:2610.03695v1 Announce Type: new Abstract: Modern chess engines are silent experts: they play at a superhuman level, but do not offer explanations for their play. On the other hand, language mode

LAS-CLIP: A Lightweight Adapter Steering Approach for CLIP's Visual Encoder

arXiv:2610.03370v1 Announce Type: new Abstract: CLIP's visual encoder produces only global image representations, limiting its use in region-level tasks. Existing adaptations rely on visual prompting,

Latent-MOPD: Latent Multi-Teacher On-Policy Distillation

arXiv:2610.02381v1 Announce Type: new Abstract: On-policy distillation (OPD) trains a student on the responses it generates. Existing LLM multi-teacher OPD transfers what specialists predict through t

Learn to optimize your own harness, folks. You can squeeze much more performance and value from a harness. This work claims that a self-modi…

Learn to optimize your own harness, folks. You can squeeze much more performance and value from a harness. This work claims that a self-modified harness matched Codex for 4.03. Specifically, a coding

model-releasesdair-ai--x

LESSER: Post-Training Data Selection with Output-Layer Gradients

arXiv:2610.03702v1 Announce Type: new Abstract: The choice of post-training data for large language models substantially affects downstream performance. Gradient-based data selection is a popular appr

Lessons learned while building Apex-2

Hi everyone, thank you so much for all the interest in my model. It's more than I expected. Here is a short summary of the trial and error I went through while building Apex-2. 1. GPUs were always the

Localized Conformal Safety Monitoring with Vision-Language Models for Autonomous Driving

arXiv:2610.02765v1 Announce Type: cross Abstract: Monitoring planned driving trajectories requires accurately estimating the collision likelihood with actors whose motion is itself impacted by the ego

LoGo: Local-Global Rewards for Consistent Long-Horizon Video Generation

arXiv:2610.03636v1 Announce Type: cross Abstract: Camera-controlled video models are rapidly advancing toward long generation horizons and complex camera control. A key failure mode is 3D inconsistenc

LPS-Bench: Benchmarking Safety Awareness of Computer-Use Agents in Long-Horizon Planning under Benign and Adversarial Scenarios

arXiv:2602.03255v2 Announce Type: replace Abstract: Computer-use agents (CUAs) execute multi-stage tasks through tools, where an early unsafe decision can propagate to consequential actions. Evaluatin

LS-AR: Future-Predictive Latent Steering in Autoregressive LLMs

arXiv:2610.03093v1 Announce Type: new Abstract: Standard autoregressive (AR) models process high-level task instructions, state history, and transient tokens within a single shared sequence of tokens.

MiDShip: Multimodal Dataset of Ship Cargo Hold Structures for Engineering Design

arXiv:2610.02214v1 Announce Type: cross Abstract: Ship structures govern vessel strength, safety, and manufacturability, but their design must satisfy hundreds of classification society requirements,

MintEval: Do LLMs Implement the Trading Strategy You Asked For? A Behavioural-Equivalence Benchmark for Natural-Language-to-Strategy Code

arXiv:2610.03080v1 Announce Type: cross Abstract: Large language models are moving from producing trading signals to writing the code that executes them. The failure mode of the second role is silent:

Mixture-of-Experts for Cryptocurrency Order Execution: Training Stability, Tail Risk, and Failure Modes

arXiv:2610.03369v1 Announce Type: cross Abstract: Deep reinforcement-learning policies for order execution can vary substantially across training seeds, so apparent architectural gains may reflect fav

MLCommons Jailbreak Benchmark v1.0

arXiv:2610.02827v1 Announce Type: new Abstract: Modern AI systems are designed to refuse hazardous requests. A jailbreak is a prompt crafted to bypass those safeguards and elicit outputs that the syst

MoE SSD streaming on a 64 GB Mac mini: GPU still waits 27% of decode on experts. Ideas?

Looking for some assistance /ideation. I am running qwen flash next q4 in my Mac mini m5 64gb. QFN doesn’t fit so this is done by having as many experts hot in cache as possible and streaming in the r

MOF-VERIFY: A Failure-Aware Agentic Harness for MOF Hypothesis Verification

arXiv:2610.03056v1 Announce Type: new Abstract: Large language models are increasingly used as reasoning components in AI-driven materials Co-Scientists, yet the reliability of the resulting verificat

Moving Forward with Video Saliency: A New Dataset and Benchmark where Motion Matters

arXiv:2610.03276v1 Announce Type: new Abstract: Video saliency prediction is inherently harder to model than static image saliency due to the additional temporal dimension. Video saliency benchmarks r

MuLoRA: Spectrally Balanced Low-Rank Adaptation for Continual Learning

arXiv:2610.02283v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) provides a parameter-efficient approach to continual learning, but its nominal rank can conceal a loss of effective adaptatio

MuonIO: Principled Norm-Aware Descent for Embedding Tables and Language Model Heads

arXiv:2610.02705v1 Announce Type: cross Abstract: The Muon optimizer derives its update rule for hidden linear layers by solving a local linearization of the loss penalized by the spectral norm, motiv

My qwen model hallucinated a signed URL to Alibaba cloud, normal or sketchy?

I'm using Qwen3.8-Flash-Next running on my Mac Studio as a daily driver for coding + productivity tasks, and yesterday it did something weird: I had it do some product research on amazon, so it was do

NegT2IBench: When Negation Changes the Picture. A Polarity Benchmark for Text-to-Image Models

arXiv:2610.03084v1 Announce Type: cross Abstract: Text-to-image (T2I) models are judged by benchmarks that measure whether requested content appears, but these benchmarks largely overlook the compleme

NeutronGym: Physics-Graded Neutron Instrument Design for LLM Agents

arXiv:2610.03631v1 Announce Type: new Abstract: Designing a scientific instrument tests whether language-model agents can do physics rather than recall it, provided the grading cannot be argued with.

New agent skill: Amazon SageMaker optimized generative AI inference for your coding agent

model-releasesaws-ml-blog

Amazon SageMaker optimized generative AI inference introduces the aws-ai-ml skill through the Agent Toolkit for AWS, giving coding agents like Kiro, Claude Code, and Codex deep expertise in inference

Objects Without Morphisms: What LLMs for Mathematics Do Not Represent

arXiv:2610.03551v1 Announce Type: new Abstract: Large language models (LLMs) have reached expert-level performance on competition mathematics largely through the volume of search placed around them: c

Ok how to actually learn vLLM ?

Said in title, I find the ecosystem difficult to understand, and RTFMing doesn't help me as it's never clear what is the server vs their client library ? I'm using it for voxtral 3B on one GPU, but it

OLMo-Detect: A Multi-Stage, Confounder-Controlled Benchmark for Membership Inference on Large Language Models

arXiv:2610.02986v1 Announce Type: new Abstract: Membership inference on large language models (LLMs) aims to determine whether a given text sample was included in an LLM's training data, without acces

OmniConfess: Eliciting Token Confessions to Mitigate Omni-Modal Hallucination

arXiv:2610.02999v1 Announce Type: new Abstract: Omni-modal large language models (OmniLLMs) unify text, images, audio, and video, yet hallucinate when generation relies on the wrong evidence. Existing

On the Chain-of-Thought Monitorability of Looped Language Models

arXiv:2610.02741v1 Announce Type: new Abstract: Chain-of-thought (CoT) monitoring provides a promising approach for detecting undesirable model behavior. Looped language models (LoopLMs) repeatedly ap

On Unlearning for Time-series Forecasting

arXiv:2610.02865v1 Announce Type: new Abstract: Time-series forecasting is widely used in sensitive domains. Models in these settings are often trained on longitudinal user- or entity-level records, w

Ontological Instability and Statistical Amplification: The Paradox of 'Humanizing' LLM-Generated Text

arXiv:2610.03110v1 Announce Type: new Abstract: Supervised AI-text detectors report high benchmark accuracy, but it is not clear what their decisions are based on. We analyze a RoBERTa-based detector

Open-Endedness Bench: Measuring Epistemic Process from Agent Records

arXiv:2610.02588v1 Announce Type: new Abstract: Agents are increasingly given open-ended research tasks: discovering an empirical law from self-designed experiments, improving a heuristic whose optimu

OpenGameEval: Benchmarking Agentic Programming and Exploration in a Stateful Game Engine

arXiv:2610.02563v1 Announce Type: cross Abstract: We present OpenGameEval, a benchmark and evaluation framework for agentic game development inside Roblox Studio. It runs language models as agents in

OpenRUA: Robot-Use Agents Are Zero-Shot Visuomotor Policies

model-releasesarxiv-cs-ro

arXiv:2610.02459v1 Announce Type: new Abstract: Coding agents are extending their reach into the physical world by writing and executing robot control programs. One might expect the agents to use the

Output Language Confusion under Multilingual Prompt Contamination

arXiv:2610.02926v1 Announce Type: new Abstract: Standard factual benchmarks assume clean monolingual prompts and exact-match scoring, two assumptions that break simultaneously in real-world multilingu

PaMIR: Open Benchmark of Public Credit-Default Datasets

arXiv:2610.03259v1 Announce Type: new Abstract: We release PaMIR (Public Arrival-ordered Measurement for Inference in Risk), an open benchmark for credit-default prediction when labels are scarce and

ParaGeo: Decomposing Paralinguistic Variation into a Shared Latent Geometry

arXiv:2610.03125v1 Announce Type: cross Abstract: Speech delivery varies with both the requested paralinguistic attribute and the linguistic content. We introduce ParaGeo, a matched-content decomposit

Parameter-Free Interval-Dynamic Regret under Heavy-Tailed Noise

arXiv:2610.02258v1 Announce Type: new Abstract: We study online convex optimization with one unbiased stochastic subgradient per round and an unknown finite conditional pth noise moment, 1<ple2. For e

Passing the Test You Trained On: Re-evaluating Prompt-Injection Detectors for LLM Agents

arXiv:2610.03448v1 Announce Type: cross Abstract: LLM agents increasingly screen tool outputs with small prompt-injection detectors, and teams choose among detectors by their scores on public benchmar