Search: “model-releases”

False Claims, Credible Images: A Red-Teaming Benchmark for Commercial Image Generators

arXiv:2610.11112v1 Announce Type: cross Abstract: Image-generation models can now produce text-rich, natural-looking visual artifacts that are hard to distinguish from real-world evidence, such as new

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Model Releases

FastBench: Can Streaming VLMs Perceive High-Dynamic Real-World Streams?

DGX agent

arXiv:2610.12427v1 Announce Type: cross Abstract: Streaming Video Large Language Models (VLMs) enable continuous video understanding, yet existing benchmarks focus on low-dynamic scenarios. Under boun

model-releasesarxiv-cs-cl

9 Oct 2026

FearCaut-Qwen: Affective Steering in a Vision-Language Model Shifts the Decision Criterion for Hazard Assessment

arXiv:2610.11986v1 Announce Type: new Abstract: Vision-language models (VLMs) show great potential for damage assessment after a disaster, but a recurring deficiency is that they are reluctant to decl

FloorSAV: Elucidating Spatial Audio-Visual Context with 2D Floormap for AV-LLMs

arXiv:2610.11310v1 Announce Type: new Abstract: While 3D spatial reasoning in dynamic egocentric environments is crucial for embodied intelligence, audio-visual large language models (AV-LLMs) lack ex

FlowState: Execution State as Memory for Long-Horizon LLM Agents

arXiv:2609.34565v2 Announce Type: replace Abstract: Long-horizon tasks require LLM agents to continually draw on information from earlier interactions. However, retaining the full history increases co

Fluid-Gen-Zero: Grounding Pretrained Video Generators in Physics without Training

arXiv:2610.10984v1 Announce Type: new Abstract: We present Fluid-Gen-Zero, a training-free framework for physics-aware fluid-object interaction video generation that decouples physical reasoning from

FlyMark: Training-Free Invisible Watermarking of 3D Gaussian Splatting via a Fruit Fly Connectome

arXiv:2610.11364v1 Announce Type: new Abstract: A trained 3D Gaussian Splatting (3DGS) scene ships as a portable parameter array that can be copied, pruned, requantized, or repackaged outside its trai

Freeze the Decoder, Heal the Encoder: Parameter-Efficient Adaptation for SVD-Based KV-Cache Compression

arXiv:2610.10552v1 Announce Type: cross Abstract: Comparing parameter-efficient fine-tuning recipes under a single, shared learning rate is a common but flawed practice: when the arms being compared h

Fresh updates for dots. First up: you can now create your dot straight from your phone in the ChatGPT app on iOS and Android.

ChatGPT introduced a new mobile feature on October 9 2026 that lets users create dots directly within the ChatGPT app on iOS and Android devices. The update adds in‑phone dot creation, streamlining wo

model-releasesopenai--x

From a Prompt to Repertoires: Evolving Functional REpertoires Enable LLM Continual Learning

model-releasesarxiv-cs-cl

arXiv:2610.11373v1 Announce Type: cross Abstract: Continual learning remains challenging for large language models, which must enable models to acquire new skills and knowledge without degrading exist

From Investigation Failures to Reliable SOC Agents: Understanding and Improving LLM-Based Alert Triage

arXiv:2610.10608v1 Announce Type: cross Abstract: Security operations centers (SOCs) must triage large volumes of alerts, most of which are benign, while missed attacks can remain uninvestigated. Tool

From Prompting to Composing: A Spatial Canvas Interface for Poster Generation

arXiv:2610.12230v1 Announce Type: cross Abstract: Text prompting is an indirect interface for poster generation, requiring users to encode inherently two-dimensional composition intent into a one-dime

From Reactive Containment to Proactive Assurance: Lessons from OpenAI, Anthropic, and Google Agent Security Incidents

arXiv:2610.12463v1 Announce Type: cross Abstract: In 2026, cybersecurity evaluations involving OpenAI, Anthropic, and Google agents reached real systems outside their authorized test scope. The paths

From Suppression to Repair: Mitigating Object Hallucination in Large Vision-Language Models via Localized Distribution Alignment

arXiv:2610.11826v1 Announce Type: cross Abstract: Object hallucination remains a major obstacle for large vision-language models (LVLMs) to generate reliable content. An intuitive mitigation strategy

From Surface to Depth: Towards Cognitive Appraisal Reasoning in Multimodal Emotion Understanding

arXiv:2610.11918v1 Announce Type: cross Abstract: Recent multimodal large language models (MLLMs) increasingly incorporate explainable reasoning for emotion understanding. However, reasoning based mai

GameCommBench: A Unified Benchmark and Type-Aware Evaluation for AI-Generated Game Commentary

arXiv:2610.11129v1 Announce Type: new Abstract: Game commentary is an open-ended generation task requiring multimodal perception, strategic reasoning, and contextual knowledge. Existing AI-Generated G

Gated Memory: Admission-Controlled Memory Formation for Conversational AI

arXiv:2610.11270v1 Announce Type: cross Abstract: Personalized conversational AI relies on long-term memory systems that extract facts from user utterances and store them in persistent vector stores.

GaussianBench: Physics-Fidelity Evaluation for Gaussian Scene Representations

arXiv:2610.10554v1 Announce Type: cross Abstract: 3D Gaussian Splatting has evolved from static reconstruction toward physics-integrated representations meant to predict how scenes change under intera

Generative Adversarial Loops

arXiv:2610.11458v1 Announce Type: cross Abstract: AI research progress can be viewed as the interaction between two processes: benchmark creation and method discovery. Historically, both were driven b

GHARP: Real-time Gaussian Head Animation from Large-scale Reconstruction Prior

arXiv:2610.10945v1 Announce Type: new Abstract: We present GHARP (Real-time Gaussian Head Animation from Large-scale Reconstruction Prior), a method that animates 3D human heads in real time from a fe

GLIO2: A GPU-Parallelized Tightly-Coupled LiDAR-Inertial-GNSS System for Robust and Real-Time Global Localization and Mapping

model-releasesarxiv-cs-ro

arXiv:2610.12411v1 Announce Type: new Abstract: Globally consistent, real-time state estimation in large-scale, perceptually degraded environments is essential for autonomous vehicles and aerial robot

GLM 5.3 Flash opensource @ the top of Artificial Analysis Cyber Index over Claude.

It seems Dario's 'too powerful for you users' strategy is paying off: we have two open models at the top of the leaderboard, surpassing every single model from Anthropic. Open source prevails. Even Mi

Google has the advantage, if they use it, of being able to observe where OpenAI and Anthropic are going with Codex/Code and get there now. O…

model-releasesethan-mollick--x

Google has the advantage, if they use it, of being able to observe where OpenAI and Anthropic are going with Codex/Code and get there now. Otherwise they are going to have to go through that whole lea

GPU-Accelerated Computation of Persistent Homology for Topological Analysis of Image Data

arXiv:2610.10959v1 Announce Type: new Abstract: In recent years, persistent homology has seen rapid adoption in deep learning, yet its computation remains a major bottleneck in network training. This

Grammar Concept Annotation at Scale: Deployed Fine-Tuned Small Language Models Outperform Prompted Frontier Models

arXiv:2610.10827v1 Announce Type: cross Abstract: Corrective feedback is among the best-evidenced drivers of second-language acquisition, yet corrections delivered during lessons rarely accumulate int

GroundSight at GroundLM 2026 Shared Tasks: GoldenViewVQA

arXiv:2610.11402v1 Announce Type: new Abstract: GoldenViewVQA requires models to jointly answer driving-scene questions and identify the camera view containing the supporting visual evidence, making p

GUI-KV: Efficient GUI Agents via KV Cache with Spatio-Temporal Awareness

model-releasesarxiv-cs-cl

arXiv:2510.00536v2 Announce Type: replace Abstract: Graphical user interface (GUI) agents built on vision-language models have emerged as a promising approach to automate human-computer workflows. How

H2O-Lightning-4B: Apache-2.0 4B Decision model, official #1 open model on JevBench (above Jev)

Disclosure: I work at H2O.ai. We released H2O-Lightning-4B, an open-weight (Apache-2.0) model for the 'decisions API' style of inference that Jev made popular: you send a state plus typed questions (p

Has LLM Screening Performance Stalled in Software Engineering Systematic Reviews?

arXiv:2610.10633v1 Announce Type: cross Abstract: Screening in systematic reviews (SRs) is manual and time-consuming. Prior work has explored large language models (LLMs) for automating this step, but

HENet++: Hybrid Encoding and Multi-task Learning for 3D Perception and End-to-end Autonomous Driving

arXiv:2511.07106v2 Announce Type: replace Abstract: Three-dimensional feature extraction and multi-task perception are fundamental components of modern autonomous driving systems. Although large image

Heterogeneous-Modal Unsupervised Domain Adaptation via Latent Space Bridging

arXiv:2506.15971v2 Announce Type: replace-cross Abstract: Unsupervised domain adaptation (UDA) effectively bridges the domain gap between a labeled source domain and an unlabeled target domain, but as

How Hackable Is Your Speech Quality Metric? A Corrected Protocol, a Benchmark, and What Patching Buys

arXiv:2610.10899v1 Announce Type: new Abstract: Speech quality predictors are increasingly used as rewards, yet no agreed measure of their hackability exists. The usual measurement has two flaws. Firs

How Narrative Wrapping Affects LLM Refusal: A Cross-Language Benchmark and Defense

arXiv:2610.11005v1 Announce Type: new Abstract: Safety-aligned language models often refuse a harmful request stated directly but answer the same request inside a role-play or narrative wrapper. We me

HRIL: Learning Multimodal Synergy via Higher-Order Tensor Modeling

arXiv:2610.12393v1 Announce Type: new Abstract: Self-supervised multimodal representation learning has achieved remarkable success across diverse domains, yet capturing synergistic information remains

Humanity's Sixth Sense: Benchmarking Intuitive Visual Reasoning in Multimodal Models

arXiv:2610.08966v2 Announce Type: replace Abstract: Humans perceive far more in a scene than what is explicitly depicted: a single glance captures past causes and future trajectories; a quick peek det

I built MaRN: a PyTorch library for training neural networks through low-dimensional parameter mappings [P]

model-releasesr-machinelearning

I built MaRN (Mapping Networks), a PyTorch library that lets you optimize a compact latent representation instead of directly training every model parameter. Some results from my current benchmarks: M

I made a portable AI memory format that transfers both context and skill

Last month I created a portable memory format as a .txt file as a small project. I named it as: Memory Journal, in a shape of a skill card. It's essentially a large prompt wrapped in a text file. Init

I’m in Seoul building Mistral’s founding Korea team. Looking for kind, ambitious researchers and engineers to build and customise LLMs for r…

model-releasesarthur-mensch--x

I’m in Seoul building Mistral’s founding Korea team. Looking for kind, ambitious researchers and engineers to build and customise LLMs for real problems, from data and evals to RL and training at scal

Informationally Decoupled Trajectory Design for Sim-to-Real System Identification

model-releasesarxiv-cs-ro

arXiv:2610.10905v1 Announce Type: new Abstract: Sampling-based system identification estimates physically meaningful parameters by tuning a simulator to reproduce the target system dynamics, providing

Instance-anchored interaction evidence: Grounding robot plans in human pointing and handling

model-releasesarxiv-cs-ro

arXiv:2610.12157v1 Announce Type: new Abstract: A robot that assists people must often act on what a person has shown rather than said: which of several identical cartons was pointed at, or which box

IntactWorld: Joint World Modeling with Intact Features

arXiv:2610.11174v1 Announce Type: new Abstract: While recent video generation models synthesize highly realistic visuals, they lack a genuine understanding of intrinsic real-world logic. Existing meth

Internalizer: Portable Context-to-Parameter Mapping for Very Large Language Models

arXiv:2610.11715v1 Announce Type: new Abstract: Hypernetworks that map a context directly to a LoRA adapter let a large language model carry that context in its weights, but prior work has demonstrate

Is In-Domain Training Enough for Fine-Grained Industrial Anomaly Understanding?

arXiv:2610.12310v1 Announce Type: new Abstract: A single multimodal large language model (MLLM) struggles to excel simultaneously at detection, localization, description, and reasoning in multimodal i

It’s Friday 🎉 Here’s a look at this week’s announcements: — http://SynthID.com is now available globally in English, allowing anyone to use…

model-releasesgoogle-ai--x

It’s Friday 🎉 Here’s a look at this week’s announcements: — http://SynthID.com is now available globally in English, allowing anyone to use our detector portal to easily verify if images, video, or au

Just another purely open-weight models benchmark

Live results, coding benchmarks included, agentic benchmarks included, domains and other classifications filters included. (Spoiler: DeepSeek-V4-Vision-Exp rules, but other models have their rule area

KDFP: A first-principles approach to knowledge distillation in large language models

arXiv:2610.10854v1 Announce Type: new Abstract: Knowledge distillation is an established technique for improving the capabilities of small, efficient student models by training them with the represent

LadderEdit: Edit-Level Residual Compression for Memory-Efficient Lifelong Editing of LLMs

model-releasesarxiv-cs-cl

arXiv:2610.11160v1 Announce Type: new Abstract: Lifelong editing of LLMs requires storing thousands of edits after acquisition. A widely used family of approaches attaches one LoRA adapter per edit, w

LAIR-Net: Leaky Alignment-Impulse Residual Networks for Tabular Regression

arXiv:2610.11538v1 Announce Type: cross Abstract: Deep randomized models fix hidden-layer parameters through random initialization and learn only closed-form readouts, typically adding depth by stacki