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I like choices... but now I have: 2x modes (Codex vs. Work mode) 3x GPT-5.6 models (Sol, Terra, Luna) 5x effort levels (Light, Medium, High,…

model-releasessebastian-raschka--x

I like choices... but now I have: 2x modes (Codex vs. Work mode) 3x GPT-5.6 models (Sol, Terra, Luna) 5x effort levels (Light, Medium, High, Extra High, Ultra) That's 2 x 3 x 5 = 30 possible configura

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I'm writing a newsletter on my favorite AI models and AI tools for every single use case. This guide is specifically written for business us…

model-releasesallie-k--miller--x

I'm writing a newsletter on my favorite AI models and AI tools for every single use case. This guide is specifically written for business users and not engineers and will help you get the most out of

LoCA: Spatially-Aware Low-Rank Convolutional Adaptation of Vision Foundation Models

arXiv:2607.06918v1 Announce Type: cross Abstract: Pre-trained Vision Foundation Models (VFMs) provide strong visual representations for diverse downstream tasks. The key challenge of VFM adaptation st

Ollama, which helps developers run open-weight AI models locally, raised a 65M Series B led by Theory Venture, following a 15M Series A led by Benchmark (Julie Bort/TechCrunch)

Julie Bort / TechCrunch: Ollama, which helps developers run open-weight AI models locally, raised a 65M Series B led by Theory Venture, following a 15M Series A led by Benchmark — The popular open sou

model-releasestechmeme

Recursive Language Models Meet Uncertainty: The Surprising Effectiveness of Self-Reflective Program Search for Long Context

Long-context handling remains a core challenge for language models: even with extended context windows, models often fail to reliably extract, reason over, and use the information across long contexts

agentsapple-ml-research

Local Ai

Reward Valuation in Vision Language Models: Causal Mechanisms Underlying Anhedonia

arXiv:2607.06626v1 Announce Type: new Abstract: Recent Vision-Language Models capture increasingly complex aspects of human cognition. Here we ask whether this alignment extends to reward valuation, w

local-aiarxiv-cs-lg

Siamese Neural Network for Label-Efficient Critical Phenomena Prediction in 3D Percolation Models

model-releasesarxiv-cs-lg

arXiv:2507.14159v2 Announce Type: replace-cross Abstract: Predicting critical phenomena from limited labeled data remains a challenging task in statistical physics. As percolation theory provides a ca

TF-Engram: A Train-Free Engram with SSD-Backed Memory for Large Language Models

model-releasesarxiv-cs-cl

arXiv:2607.07388v1 Announce Type: new Abstract: Large Language Models (LLMs) store factual knowledge and domain-specific patterns implicitly in dense Transformer parameters, making knowledge expansion

Vision Language Action (VLA) Models for Unmanned Aerial Robotics and Bimanual Manipulation: A Review

arXiv:2607.06706v1 Announce Type: cross Abstract: Vision Language Action (VLA) models unify visual perception, natural-language understanding, and action generation within a single foundation model, a

researcharxiv-cs-ai

Yesterday we launched SWE-1.7 built on the open-source Kimi K2.7. Concerns about Chinese base models are real: K2.7 completed 87% of tasks t…

Yesterday we launched SWE-1.7 built on the open-source Kimi K2.7. Concerns about Chinese base models are real: K2.7 completed 87% of tasks that other models refuse over human-rights concerns. We train

agentscognition-ai--x

ExplAIner: A Declarative Query Language for Explaining Classification Models

arXiv:2607.06407v1 Announce Type: new Abstract: The XAI community has studied a wide range of queries and scores for explaining predictions of ML models. From a data management perspective, this proli

researcharxiv-cs-ai

Applications

Learning 4D Geometric Priors for Inference-Efficient World Action Models

arXiv:2607.05468v1 Announce Type: cross Abstract: World Action Models (WAMs) have shown strong potential for robotic manipulation by jointly modeling visual future dynamics and executable action seque

applicationsarxiv-cs-ai

Parameter-Free Encoders Remain Viable for RDB Foundation Models

model-releasesarxiv-cs-lg

arXiv:2607.05476v1 Announce Type: new Abstract: Given a relational database (RDB) storing heterogeneous tabular information, how can we predict missing (or future) values in some target column of inte

RPAM: A Principled Metric for Evaluating Associations in Language Models with High Predictive Validity in Downstream Outputs

arXiv:2607.05679v1 Announce Type: cross Abstract: Language models (LMs) exhibit problematic biases, such as stereotypes. Effectively analyzing and mitigating such biases requires accurate and generali

These new models are rolling out to everyone over the next few days, starting today. They’ll be available in ChatGPT across iOS, Android, an…

These new models are rolling out to everyone over the next few days, starting today. They’ll be available in ChatGPT across iOS, Android, and web. Coming soon to the API. Just tap the Voice button to

model-releasesopenai--x

Deep Learning Network-Temporal Models For Traffic Prediction

arXiv:2603.11475v2 Announce Type: replace Abstract: Accurate prediction of multivariate time series is essential for emerging network intelligent control, observability, and management functions. Exis

researcharxiv-cs-lg

Diffusion Models are Open-World Affordance Learners: Leveraging Generative Priors for 3D Affordance Learning

arXiv:2508.01651v2 Announce Type: replace Abstract: 3D affordance grounding aims to understand how diverse objects can be manipulated, making it a cornerstone of embodied interaction. However, prior w

Heaviside Continuity of Rolling Coefficients for Eliminating Epistemic Entropy in Large Language Models

arXiv:2607.04562v1 Announce Type: new Abstract: Large language models (LLMs) generate fluent outputs that can be wrong. Unlike humans, who often exhibit cues when providing false information, LLMs pro

agentsarxiv-cs-ai

Is the Geometry Doing the Work? An Operating-Point Audit of Hierarchy in Hyperbolic Vision-Language Models

arXiv:2607.05268v1 Announce Type: new Abstract: Whether a hyperbolic representation model uses its geometry cannot be read off its curvature parameter: what matters is the dimensionless operating poin

Mitigating Covariate Shift in Imitation Learning for Autonomous Vehicles Using Latent Space Generative World Models

arXiv:2409.16663v5 Announce Type: replace-cross Abstract: We propose the use of latent space generative world models to address the covariate shift problem in autonomous driving. A world model is a ne

safetyarxiv-cs-cv

Out-of-Distribution Generalization of Risk Aversion in Language Models

arXiv:2607.02755v1 Announce Type: cross Abstract: Training AIs to be risk-averse in resources could offer a failsafe in the event that AIs turn out misaligned. Misaligned but risk-averse AIs would ten

Parameter Efficient Multimodal Instruction Tuning for Romanian Vision Language Models

arXiv:2512.14926v2 Announce Type: replace-cross Abstract: Focusing on low-resource languages is an essential step toward democratizing generative AI. In this work, we contribute to reducing the multim

PuzzleMoE: Efficient Compression of Large Mixture-of-Experts Models via Sparse Expert Merging and Bit-packed inference

arXiv:2511.04805v2 Announce Type: replace-cross Abstract: Mixture-of-Experts (MoE) models have shown strong potential in scaling language models efficiently by activating only a small subset of expert

researcharxiv-cs-ai

Reducing the Complexity of Deep Learning Models for EEG Analysis on Wearable Devices

arXiv:2606.12742v3 Announce Type: replace Abstract: Wearable healthcare devices are the fastest-growing Internet of Things (IoT) sector. Many automated healthcare services rely on two crucial biologic

Reward Granularity in RLVR: Comparing Process and Outcome Reward Structures for Mathematical Reasoning in Small Language Models

arXiv:2607.02869v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has emerged as a promising paradigm for improving mathematical reasoning in language models. Yet m

safetyarxiv-cs-lg

Local Ai

Stage-wise Attention-Guided Region Sequencing for Adversarial Attacks on Large Vision-Language Models

arXiv:2602.04356v2 Announce Type: replace Abstract: Targeted adversarial attacks on Large Vision-Language Models (LVLMs) test whether small image perturbations can steer model responses toward attacke

local-aiarxiv-cs-cv

Taming I2V models for Image HOI Editing: A Cognitive Benchmark and Agentic Self-Correcting Framework

arXiv:2606.19073v2 Announce Type: replace Abstract: Current image editing methods excel at static attributes but fail at complex Human-Object Interactions (HOI), a critical challenge unaddressed by ex

Applications

World models are very interesting. https://x.com/connerruhl/status/2074245101379846400?s=20

applicationsethan-mollick--x

World models are very interesting. https://x.com/connerruhl/status/2074245101379846400?s=20 Do world models work as a medium for storytelling? Over the weekend, I wanted to see how far I could push re

Run MiniMax models on Amazon Bedrock

In this post, we walk through how to get started with MiniMax models on Amazon Bedrock, including the capabilities supported by these models, the service tiers available, how on-demand inference scale

agentsaws-ml-blog

6 Jul 2026

As America turns 250, we put together 250 open AI milestones from the US: open models, datasets, demos, papers, and tools that helped shape …

model-releasesclem-delangue--x

As America turns 250, we put together 250 open AI milestones from the US: open models, datasets, demos, papers, and tools that helped shape the field. They go from attention is all you need, pytorch,

4 Jul 2026

Automated grading of Linux/bash examinations using large language models: a four-level cognitive taxonomy approach

arXiv:2607.02432v1 Announce Type: new Abstract: Scalable and reliable grading of command-line examinations remains a challenge in computing education, where rising enrolments make manual marking diffi

Certified World Models as Sensing Clocks: Drift-Aware Deadlines for Active Perception

arXiv:2607.01537v1 Announce Type: new Abstract: Certified world models estimate how long their predictions remain valid. We turn this validity horizon into an operational sensing clock: a rule for whe

agentsarxiv-cs-lg

Generic Expert Coverage for Pruning SparseMixture-of-Experts Language Models

arXiv:2607.01710v1 Announce Type: new Abstract: Sparsely activated Mixture-of-Experts (MoE) language models contain substantial structured redundancy among routed experts, but pruning them without dow

Neuro-Symbolic Safety Guidance for Vision-Language-Action Models via Constrained Flow Matching

model-releasesarxiv-cs-ro

arXiv:2607.01378v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have demonstrated promising generalization capabilities across robotic manipulation tasks, yet their real-world depl

SAB-LVLM: Significance-Aware Binarization for Large Vision-Language Models

arXiv:2607.01876v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable progress in multimodal understanding, yet their enormous parameter scale and cross-modal

StatEval: A Comprehensive Benchmark for Large Language Models in Statistics

model-releasesarxiv-cs-cl

arXiv:2510.09517v2 Announce Type: replace Abstract: Despite rapid advances in large language models (LLMs), statistical reasoning remains underrepresented in existing LLM benchmarks, which often do no

AdaBoosting Text Prompts for Vision-Language Models

arXiv:2607.00684v1 Announce Type: new Abstract: The classification accuracy of pretrained Vision-Language Models (VLMs) relies on the quality of the text prompts. Handcrafted templates and Large Langu

researcharxiv-cs-lg

Enhanced Vision-Language Models for Diverse Sensor Understanding: Cost-Efficient Optimization and Benchmarking

arXiv:2412.20750v3 Announce Type: replace Abstract: Large-scale Vision-Language Models (VLMs) have achieved notable progress in aligning visual inputs with text. However, their ability to deeply under

ext{Log}_ext{b}Quant: Quantizing Language Models in Logarithmic Space

model-releasesarxiv-cs-cl

arXiv:2607.01127v1 Announce Type: new Abstract: Quantization has become an invaluable tool to reduce memory requirements and inference speed of modern language models, in particular to make them avail

LongVQUBench: Benchmarking Long-Term Video Quality Understanding of Vision-Language Models

arXiv:2607.01086v1 Announce Type: cross Abstract: The evaluation of long-term video quality understanding remains an open challenge for large vision-language models (LVLMs). Existing video quality ben

NeuroCogMap Reveals Cognitive Organization of Large Language Models

arXiv:2607.00397v1 Announce Type: cross Abstract: Understanding how complex cognitive functions are organized within artificial systems is central to interpreting large language models (LLMs) and rela

safetyarxiv-cs-ai

Reasoning Up the Instruction Ladder for Controllable Language Models

arXiv:2511.04694v5 Announce Type: replace-cross Abstract: As large language model (LLM) based systems take on high-stakes roles in real-world decision-making, they must reconcile competing instruction

safetyarxiv-cs-ai

Recovering Input Text from Hidden States: Study of Gradient-Based Inversion of Decoder-Only Language Models

arXiv:2607.00852v1 Announce Type: cross Abstract: This work studies the hidden-state inversion problem: recovering the original input token sequence of a decoder-only language model from its last-laye

Applications

Tripo AI secures additional $150M in funding to enhance its 3D and world models

Tripo AI, a developer of interactive 3D foundation models and world models, said today it has closed on a hefty 150 million Series A3 funding round to scale up its platform in the intelligent manufact

applicationssiliconangle

What's Hidden Matters: Identifying Planning-Critical Occluded Agents using Vision-Language Models

arXiv:2607.00283v1 Announce Type: cross Abstract: Autonomous vehicles must safely navigate complex environments where planning-critical agents may be hidden from view. Current approaches often treat a

Cross-lingual Relation Extraction with Large Language Models: Zero-Shot, Few-Shot, and Fine-Tuned Evaluation on Romanian

arXiv:2606.31718v1 Announce Type: cross Abstract: Relation extraction (RE) for low-resource languages is typically constrained by the lack of annotated corpora. We investigate the feasibility of cross

1 Jul 2026

How (Not) to Hybridize Neural and Mechanistic Models for Epidemiological Forecasting

arXiv:2602.06323v2 Announce Type: replace Abstract: Epidemiological forecasting from surveillance data is a hard problem and hybridizing mechanistic compartmental models with neural models is a natura

researcharxiv-cs-lg

1 Jul 2026

Multi-GPU kernels are the real test for coding models. Today at @aiDotEngineer, @simran_s_arora shared ParallelKernelBench, an open-source b…