model releases

Triple-Bottom-Line Sustainability of Language Models for Edge AI: A Comparison Between SLMs and Quantized LLMs

arXiv:2609.00665v1 Announce Type: new Abstract: Edge-AI model selection is commonly driven by one isolated metric - accuracy, latency, memory, energy, or safety, even though a deployable language mode

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Model Releases

TWIX: a Two-Stage Approach for End-To-End Named Entity Recognition and Relation Extraction

DGX agent

arXiv:2609.00832v1 Announce Type: new Abstract: The exponential growth of scientific publications calls for automatic Information Extraction (IE) systems to support knowledge discovery. In this contex

model-releasesarxiv-cs-cl

2 Sept 2026

UI-Venus-2 Technical Report

arXiv:2609.00028v1 Announce Type: new Abstract: Multimodal GUI agents have emerged as a promising paradigm for digital task automation, yet transitioning from benchmark-oriented models to dependable r

Uncovering the Computational Ingredients of Human-Like Representations in LLMs

arXiv:2510.01030v2 Announce Type: replace Abstract: The human ability to translate diverse perceptual and linguistic inputs into structured behavior has been thought to rest on learning robust represe

v0.33.3

model-releasesollama-releases

Ollama released version v0.33.3 on September 2, 2024, based on commit 5ec5804 and signed with GitHub’s verified signature (GPG key B5690EEEBB952194). Key changes include default parameter definitions

Value analysis of the old Ollama Pro sub model vs the new per-token model (from 50 days of real usage)

Why I have this data: one Pro account kept hitting limits, so I run three Pro subs through 9router, a self-hosted router that sits between my coding tools and ollama cloud. It spreads requests across

model-releasesr-ollama

Variance-Adaptive Muon: Pre-Orthogonalization Variance Modulation for Efficient Language Model Pretraining

arXiv:2601.14603v2 Announce Type: replace Abstract: Optimizer design plays a central role in efficient language model pretraining, directly affecting optimization dynamics, convergence speed, and comp

VectorGym: A Multi-Task Benchmark for SVG Code Generation, Sketching and Editing

arXiv:2603.29852v2 Announce Type: replace-cross Abstract: We introduce VectorGym, a comprehensive benchmark suite for Scalable Vector Graphics (SVG) that spans generation from text and sketches, compl

VerNav: Verifier-First Low-Latency Vision-and-Language Navigation

arXiv:2609.00920v1 Announce Type: cross Abstract: Vision-and-Language Navigation (VLN) requires an agent to navigate through unseen 3D environments according to natural-language instructions. Explicit

VIBE-Bench: Evaluating Personalized Large Language Models When Profiles Don't Mean Preferences

arXiv:2609.00921v1 Announce Type: new Abstract: Personalized Large Language Models (PLLMs) aim to tailor responses to individual users, where a central challenge is preference reasoning: inferring que

ViPlan: A Benchmark for Visual Planning with Symbolic Predicates and Vision-Language Models

arXiv:2505.13180v3 Announce Type: replace Abstract: Integrating Large Language Models with symbolic planners is a promising direction for obtaining verifiable and grounded plans, with recent works ext

ViTAL-X: Video-Text Alignment with Cross-Modal Temporal Edits

arXiv:2609.00505v1 Announce Type: new Abstract: Video-text models adapted from image-text architectures (e.g., CLIP) frequently exhibit temporal blindness, the inability to perceive fundamental cues l

VoiceLongMemEval: Do Assistants Remember How You Sounded?

arXiv:2609.00570v1 Announce Type: new Abstract: With the growing scale of multi-agent architectures and large language models, deployed AI assistants are increasingly tasked with reasoning over long,

VoxGen, an AMD-optimized TTS inference engine for VoxCPM 2 models

model-releasesr-localllama

Hi, everyone, I’ve just released VoxGen, a lightweight native inference engine for VoxCPM2, written in Rust and using Vulkan compute instead of Python/PyTorch/CUDA. Why VoxGen? The main reason I start

Wave Function Backpropagation with Explicit Temporal-Interval Dynamics

arXiv:2609.00503v1 Announce Type: new Abstract: Conventional neural networks learn predominantly through affine transformations followed by nonlinear activations, while elapsed time is often treated a

We benchmark Qwen3.6-35B-A3B on an M5 Max MacBook Pro. Across ten prompt lengths and ten decode contexts, Lily was faster than MLX-LM, avera…

model-releasesperplexity--x

We benchmark Qwen3.6-35B-A3B on an M5 Max MacBook Pro. Across ten prompt lengths and ten decode contexts, Lily was faster than MLX-LM, averaging 1.23× higher prefill throughput and 1.35× higher decode

We’re introducing Gemini 3.8 Flash ⚡️ built to tackle complex agentic and multi-step tasks with even greater diligence. Our most intelligent…

model-releasesgoogle-ai--x

We’re introducing Gemini 3.8 Flash ⚡️ built to tackle complex agentic and multi-step tasks with even greater diligence. Our most intelligent workhorse model yet delivers significant improvements in re

What Does an Agentic Software Engineering Benchmark Measure? Profiling Task Demands and Agent Behaviour Beyond What Category Labels Reveal

arXiv:2609.01271v1 Announce Type: cross Abstract: Agentic software engineering benchmarks are typically summarized by nominal category labels such as 'bug fix' or 'feature implementation,' yet benchma

When Does Online Adaptation Pay on the Edge? A Leakage-Free Evaluation of Warmup, Learning-Rate Selection, and Resource Trade-offs for Time-Series Forecasting

arXiv:2609.01126v1 Announce Type: new Abstract: Online adaptation can help edge time-series forecasting under distribution drift, but its measured benefit is sensitive to evaluation choices. We study

When Features Become Instances: Inverted Contrastive Learning for Unsupervised Feature Selection

arXiv:2609.00782v1 Announce Type: new Abstract: Unsupervised feature selection seeks a compact subset of informative features without access to class labels, making feature utility difficult to define

Where the Verifier Fails: A Category-Level Audit of Reward Signals in RLVR

arXiv:2609.01354v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) and standard benchmark evaluation both rely on an automatic verifier that turns a free text answer

Which one will you choose and why, between R9700 32GB vs W7800 48GB?

model-releasesr-localllama

I'm planning to upgrade my workstation (linux with 5700X/64GB DDR4) for local inference and pytorch training. I'm trying to decide between: 2× AMD Radeon AI PRO R9700 32GB 2× AMD Radeon PRO W7800 48GB

Who Judges the Judges? A Chinese Safety QA Benchmark for Evaluating LLM Responses and Safety Judges

arXiv:2609.01210v1 Announce Type: cross Abstract: Safety benchmarks for large language models often assess the risk of a user query, although the outcome of question answering depends on whether the r

Will this server hardware work?

Years ago I built a server, shelved it after some time, but recently realized I have it sitting there. I'm looking to pop in a Tesla V100 32GB card (with proper cooling). But are the component too old

model-releasesr-ollama

WorldBench: Culturally Grounded Benchmark for Multilingual Agents

arXiv:2609.01056v1 Announce Type: new Abstract: Despite the growing use of LLM-powered agents to solve multi-step tasks in complex environments, existing benchmarks rarely test state preservation, per

Your favorite fastest abliterated/safety removed 3.6 and 3.8 27b?

model-releasesr-localllama

Not written by AI all mistakes mine. I saw people on the subreddit saying that 3.6 works better without thinking. It made me want to know for certain about which is better, 3.6 or 3.8 for low thinking

ZeroDrift launches service to check agent-generated messages against company policies

model-releasessiliconangle

ZeroDrift Inc., a startup that automates compliance for artificial intelligence communications, today introduced Guard for Agents, a service that lets developers turn written company policies into enf

A Calibration Audit of Confidence in Feed-Forward 3D Reconstruction

arXiv:2608.29705v1 Announce Type: cross Abstract: Feed-forward 3D reconstruction models emit a per-pixel confidence that downstream systems read as a reliability signal. It is trained as a loss weight

A Causal Model for Locating and Unlocking Sandbagging in Model Organisms

arXiv:2608.29461v1 Announce Type: new Abstract: Sandbagging models strategically underperform on evaluations while retaining the capabilities being measured. The evaluations that guide frontier-model

A collective capability boundary in frontier large language models on guideline-conformant and case-specific oncology decision-making

arXiv:2608.28592v1 Announce Type: new Abstract: Large language models (LLMs) achieve high scores on medical knowledge examinations, yet real-world oncology is not a knowledge test--it is a sequence of

A Composition-Aware Pretraining Framework for Geospatial Foundation Models

arXiv:2608.30817v1 Announce Type: cross Abstract: Geospatial foundation models have emerged as state-of-the-art methods for downstream Earth observation tasks. However, existing pretraining methodolog

A Degradation-Tolerance Benchmark for Camera-Only End-to-End Driving

model-releasesarxiv-cs-ro

arXiv:2608.29005v1 Announce Type: new Abstract: Camera-only end-to-end (E2E) driving models are nearing deployment, where the camera stream is degraded by blur, noise, low light, weather, frame loss,

A Hub of Short Rows Inflates Intrinsic Dimension Estimation of Token Embeddings

arXiv:2608.29702v1 Announce Type: new Abstract: A token-embedding table holds a hub of short rows near its origin, and we show that this cluster biases what nearest-neighbor intrinsic-dimension (ID) e

A Model with No Head and Many Thoughts

arXiv:2608.31069v1 Announce Type: cross Abstract: Large language models decode by projecting hidden states through a large vocabulary head at every step. This operation is computationally costly and f

A Study of the Design Space of Motion and Disocclusion Control in Video Generation

arXiv:2512.13392v3 Announce Type: replace Abstract: Disocclusion occurs when object movement reveals previously hidden content. Existing image-to-video methods provide different forms of motion and di

A Universal Context-Reuse Layer for Cross-Model KV Sharing

arXiv:2608.30963v1 Announce Type: cross Abstract: Modern large language model (LLM) serving systems increasingly operate over repeated or shared context, yet each model typically performs its own pref

ActiveAugment: Online Active Learning for Augmentation Selection in Deep Learning

arXiv:2608.28923v1 Announce Type: cross Abstract: Data augmentation is a cornerstone of deep learning pipelines, yet existing strategies treat it as a static, model-agnostic preprocessing step, either

AdaPath: Query-Adaptive Path-Finding via Path-Bank for Multi-Hop Implicit Biomedical KGQA

arXiv:2608.30556v1 Announce Type: new Abstract: Path-finding over knowledge graphs has become an effective way to ground LLM reasoning on multi-hop questions. However, biomedical QA introduces two dis

AdaVLA: Adaptive Step Flow Matching for Training-free Acceleration of Vision-Language-Action Models

arXiv:2608.29208v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models, built upon Vision-Language Models (VLMs), have significantly enhanced robotic capabilities by leveraging internet

Adversarial Calibration Attack on Autonomous Vehicles

arXiv:2608.28778v1 Announce Type: cross Abstract: Autonomous vehicles (AVs) rely on accurate camera-LiDAR calibration for multimodal sensor fusion. In practice, calibration can drift due to vibration,

After raising $10M in funding, Visko debuts Orbis, its first live model for generating long-form videos

model-releasessiliconangle

Visko Platform Inc., an artificial intelligence research lab focused on developing persistent world models, said today it has raised 10 million in a pre-seed funding round from Llama Ventures. It’s al

AgenTRIM: Tool Risk Mitigation for Agentic AI

arXiv:2601.12449v2 Announce Type: replace-cross Abstract: AI agents are autonomous systems that combine LLMs with external tools to solve complex tasks. While such tools extend capability, improper to

AgentRx: Diagnosing AI Agent Failures from Execution Trajectories

arXiv:2602.02475v2 Announce Type: replace Abstract: AI agents often fail in ways that are difficult to localize because executions are probabilistic, long-horizon, multi-agent, and mediated by noisy t

AGM: Achievement-Grounded Memory for Closed-Loop Agents with Frozen VLA Policies

arXiv:2608.29537v1 Announce Type: cross Abstract: Frozen vision-language-action (VLA) policies offer broad manipulation skills but execute open-loop action chunks without tracking task progress, so th

Agnostics: Learning to Code in Any Programming Language via Reinforcement with a Universal Learning Environment

arXiv:2508.04865v4 Announce Type: replace Abstract: Large language models (LLMs) already excel at writing code in high-resource languages such as Python and JavaScript, yet stumble on low-resource lan

AI Historian: Helping historians organize and verify person-centred temporal clues from dispersed historical narratives

arXiv:2608.29133v1 Announce Type: new Abstract: History is not preserved in complete, continuous form. Accounts of a person's activities, relationships and historical contexts are scattered across tex

Alert: Learning Trigger Functions for Early Classification of Time Series using Deep-RL

arXiv:2502.06584v2 Announce Type: replace Abstract: Early Classification of Time Series (ECTS) is vital in fields like industrial monitoring and medical triage, where quick and accurate predictions ar

AlgoWorlds: Benchmarking Tool Use for Global Optimization in Algorithmic Worlds

arXiv:2608.29397v1 Announce Type: new Abstract: Tool-use benchmarks generally evaluate whether an agent completes a workflow using appropriate tools and valid arguments. However, feasibility alone is