Search: “models”

How Learning Dynamics Drive Adversarially Robust Generalization?

arXiv:2410.07719v4 Announce Type: replace Abstract: Despite being widely adopted as a canonical framework for learning robust models, adversarial training suffers from robust overfitting. Existing emp

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Information Allocation Dynamics in Neural Network Optimization

DGX agent

arXiv:2607.07156v1 Announce Type: new Abstract: Different optimizers have different update biases, but these biases are usually implicit. Existing studies mainly analyze or control such biases from th

model-releasesarxiv-cs-lg

9 Jul 2026

Interesting comparison of Grok & Opus 1M+ context window coming soon

model-releaseselon-musk--x

Elon Musk announced an upcoming comparison between Grok and Anthropic's Claude Opus with its 1M+ token context window. The post suggests xAI plans to demonstrate how Grok's capabilities compare to Cla

Agents

Introducing Muse Spark 1.1

Introducing Muse Spark 1.1 Following Muse Spark in April, here's Muse Spark 1.1 - the first Spark model to offer an API. Meta claim significant improvements in agentic tool calling and computer use. T

agentssimon-willison

Latent graph encoding of multimodal neuroimaging features with generative AI architectures

arXiv:2607.07027v1 Announce Type: cross Abstract: While generative models enable encoding of complex neuroimaging data for feature generation and reconstruction, developing optimal architectural frame

researcharxiv-cs-ai

LEMUR 2: Unlocking Neural Network Diversity for AI

arXiv:2607.06839v1 Announce Type: cross Abstract: Existing NAS benchmarks (e.g., NAS-Bench, NATS-Bench) cover only narrow, task-specific regions of the architectural design space and lack cross-domain

researcharxiv-cs-cv

Measuring the metacognition of AI

arXiv:2603.29693v3 Announce Type: replace Abstract: A robust decision-making process must take into account uncertainty, especially when the choice involves inherent risks. Because artificial intellig

Meet Bartosz (@nasqret). A mathematician solving previously unsolvable math problems with GPT-5.6

Bartosz (@nasqret) is a mathematician who uses GPT-5.6 to solve mathematical problems that were previously considered unsolvable or intractable. This case study from OpenAI highlights how advanced lar

model-releasesopenai--x

Optimization Geometrodynamics: A Framework for Dynamic Geometric Optimization

arXiv:2607.06723v1 Announce Type: cross Abstract: Most gradient-based optimization methods move parameters through a fixed background geometry, even when their internal states implicitly define changi

PeTeR: Post-Training Robustification of Probabilistic Circuits

arXiv:2607.07671v1 Announce Type: new Abstract: Probabilistic circuits (PCs) can model complex joint distributions while supporting exact and efficient computation of many inference queries. However,

Local Ai

PRoVeFL: Private Robust and Verifiable Aggregation in Federated Learning

arXiv:2607.06612v1 Announce Type: cross Abstract: Federated Learning (FL) enables multiple clients to collaboratively train machine learning models while retaining data locality, thereby enhancing use

local-aiarxiv-cs-ai

Agents

Reliable and Developer-Aligned Evaluation of Agents for Software Engineering

arXiv:2607.06713v1 Announce Type: cross Abstract: Large language models are rapidly moving towards closing the development cycle, transitioning from simple assistive companions to autonomous contribut

agentsarxiv-cs-ai

Restricted Dynamic Geometric Complexity: Certificates for Structured Preconditioning

arXiv:2607.07204v1 Announce Type: cross Abstract: Optimization geometrodynamics views optimizer state as evolving geometry. Its full positive-definite quadratic benchmark gives the least affine-invari

RL Post-Training Builds Compositional Reasoning Strategies

arXiv:2607.07646v1 Announce Type: new Abstract: Does RL post-training merely amplify primitive skills already latent in a base model, or can it compose primitive skills into new higher-level strategie

researcharxiv-cs-ai

Sparse Delta Memory: Scaling the State of Linear RNNs through Sparsity

arXiv:2607.07386v1 Announce Type: new Abstract: Linear attention models allow a fixed state size and a fixed amount of compute per token. However, due to their limited state size, linear attention mod

Structural Adversarial Attacks on Relational Deep Learning under Integrity Constraints

arXiv:2607.07089v1 Announce Type: new Abstract: Relational Deep Learning (RDL) has become a standard methodology for machine learning on relational databases: the database is encoded as a heterogeneou

Hardware

Synthetic Data Generation for Financial AI Research with NVIDIA NeMo

NVIDIA's NeMo framework addresses the challenge of limited, imbalanced financial NLP data by generating synthetic financial news headlines to fill gaps for trading research, risk modeling, and surveil

hardwarenvidia-developer

T^{3}S: Think in Thermal Time for Generalizable Crop Mapping from Satellite Image Time Series

model-releasesarxiv-cs-cv

arXiv:2506.12885v4 Announce Type: replace Abstract: Crop type classification from optical satellite time series remains limited in its ability to generalize across growing seasons, particularly when c

To be frank, at @QodoAI we were cautious about the last few GPT-5.x upgrades. GPT-5.6 is a clear-cut upgrade. Better code-review quality, fe…

model-releasesitamar-friedman--x

To be frank, at @QodoAI we were cautious about the last few GPT-5.x upgrades. GPT-5.6 is a clear-cut upgrade. Better code-review quality, fewer tokens, lower latency. @OpenAI cooked here. obviously th

When Distillation Breaks Motion Control: Restoring Generative Trajectories for Fast Video Generators

arXiv:2506.19348v2 Announce Type: replace Abstract: Training-free motion customization imposes motion patterns from reference videos onto video generators through test-time computation. Most existing

researcharxiv-cs-cv

Tutorials

A Convex Approximation Framework for Neural Likelihood-Based Bayesian Inverse Problems

arXiv:2607.06252v1 Announce Type: cross Abstract: Many problems in science and engineering are difficult to model accurately, either due to unknown physical mechanisms, poorly quantified measurement u

tutorialsarxiv-cs-lg

A VLM-Enhanced Framework for Comprehensive Traffic Sign Condition Assessment Integrating Daytime Visual Performance and Nighttime Retroreflectivity Evaluation

model-releasesarxiv-cs-cv

arXiv:2607.06478v1 Announce Type: new Abstract: Traffic signs are crucial components of road safety, serving as visual tools under all lighting conditions. The Manual on Uniform Traffic Control Device

Added Grok 4.5 to the Harbor Town Playable gallery. Here is it's 'build me a procedurally generated 3D simulation showing the evolution of a…

model-releasesethan-mollick--x

Added Grok 4.5 to the Harbor Town Playable gallery. Here is it's 'build me a procedurally generated 3D simulation showing the evolution of a harbor town from 3000 BCE to 3000 AD, it should look beauti

Applications

AlayaWorld: Long-Horizon and Playable Video World Generation

arXiv:2607.06291v1 Announce Type: new Abstract: Game worlds have traditionally been built through labor-intensive production pipelines, making them costly to develop, difficult to customization, and e

applicationsarxiv-cs-cv

Local Ai

Analysis-by-Proxy: Localization Signals in VLMs Operating as Condition Encoders

arXiv:2607.06445v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) are increasingly utilized as the conditioning backbone for diffusion-based image editing due to their remarkable multimo

local-aiarxiv-cs-ai

APVI-SLAM: Real-Time Acoustic-Pressure-Visual-Inertial Localization and Photorealistic Mapping System in Complex Underwater Environment

model-releasesarxiv-cs-ro

arXiv:2607.06222v1 Announce Type: new Abstract: Extreme subsea environments often cause severe feature de-gradation and estimator divergence in underwater visual-inertial SLAM. Although sensors like D

Auditing of Unlearning Algorithms

arXiv:2607.05898v1 Announce Type: new Abstract: Evaluating whether unlearning algorithms truly remove training data influence remains an open challenge. We propose a practical auditor that computes da

Automated Compliance Mapping in Cloud Security with Domain-Adapted Sentence Transformers

arXiv:2607.06364v1 Announce Type: new Abstract: Mapping cloud security controls to technical metrics is currently a manual process. This paper proposes domain adaptation of Sentence Transformer models

researcharxiv-cs-cl

BabyVision: Visual Reasoning Beyond Language

model-releasesarxiv-cs-cl

arXiv:2601.06521v2 Announce Type: replace-cross Abstract: While humans develop core visual skills long before acquiring language, contemporary Multimodal LLMs (MLLMs) still rely heavily on linguistic

Beyond Heuristic Tuning: Power-Calibrated LLM Watermarking

arXiv:2607.05694v1 Announce Type: cross Abstract: Logit-based watermarking is a widely used mechanism for identifying LLM generated content, yet its effectiveness is governed by a fundamental trade-of

Bridging Physical Reasoning and Task Generalization via Visual Action Outcome Reasoning Alignment

arXiv:2607.06522v1 Announce Type: new Abstract: Vision-language models (VLMs) struggle to generalize in interactive physical reasoning, particularly under unseen tasks and environments. Two key failur

Broken Ergodicity and the Violation of the Fluctuation-Dissipation Theorem Lead to Generalization Beyond Overfitting in Machine Learning

arXiv:2607.04135v1 Announce Type: cross Abstract: The remarkable ability of modern neural networks to generalize improves with increasing network capacity, even when the number of model parameters or

Busy couple days ahead! Today, @nvidia Nemotron 3 Ultra support for @LangChain Deep Agents at a fraction of the cost -w/ Quick Start Prompt …

model-releasesharrison-chase--x

Busy couple days ahead! Today, @nvidia Nemotron 3 Ultra support for @LangChain Deep Agents at a fraction of the cost -w/ Quick Start Prompt Tomorrow is Wikimania🔥 @hwchase17 is chatting with with @Bra

Cognition releases SWE-1.7, trained from Kimi K2.7 and available at 1,000 tokens/second, claiming it nears GPT-5.5 and Opus 4.8 on benchmarks at a lower cost (Cognition)

Cognition: Cognition releases SWE-1.7, trained from Kimi K2.7 and available at 1,000 tokens/second, claiming it nears GPT-5.5 and Opus 4.8 on benchmarks at a lower cost — Today, we're launching SWE-1.

model-releasestechmeme

Controlling Tool Use with Heading-Specific Activation Steering

arXiv:2607.05790v1 Announce Type: new Abstract: Tool-augmented large language models extend their capabilities beyond parametric knowledge through external tools, but tend to invoke them unnecessarily

Decoding the Multimodal Mind: Generalizable Brain-to-Text Translation via Multimodal Alignment and Adaptive Routing

model-releasesarxiv-cs-cl

arXiv:2505.10356v3 Announce Type: replace Abstract: Decoding language from the human brain remains a grand challenge for Brain-Computer Interfaces (BCIs). Current approaches typically rely on unimodal

Differentially Private Natural Gradient Descent

arXiv:2607.05866v1 Announce Type: cross Abstract: Under a fixed privacy budget, the utility of differentially private (DP) training is ultimately determined by its optimization efficiency. Standard fi

DT-Guard: Intent-Driven Reasoning-Active Training for Reasoning-Free LLM Safety Guardrail

arXiv:2607.06326v1 Announce Type: new Abstract: Large language models deployed in open-world applications require safety guardrails that are both robust to complex risks and efficient enough for low-l

EAGOR: Embodied Reasoning in Omni-direction

model-releasesarxiv-cs-ro

arXiv:2607.06165v1 Announce Type: new Abstract: Omni-directional (360{eg}) cameras provide embodied agents with a holistic view of their surroundings, making them suited for directional reasoning in t

ELSA3D: Elastic Semantic Anchoring for Unified 3D Understanding and Generation

arXiv:2607.06565v1 Announce Type: cross Abstract: Unified 3D foundation models aspire to generate 3D assets and reason about them in language within a single backbone, but their text-3D interaction re

Empirical Minimal-Realisation Compression of Deep Neural Networks via Controllability-Observability Tests

arXiv:2607.05457v1 Announce Type: cross Abstract: Deep neural networks often contain substantial hidden-state redundancy, but most compression methods operate directly on weights, neurons, or quantise

Entanglement as a Structural Complexity Axis: A PAC-Bayesian View of Generalization in Quantum Policies and Value Functions

arXiv:2607.06230v1 Announce Type: cross Abstract: Parameterized quantum circuits (PQCs) are increasingly used as policies and value functions in quantum reinforcement learning, yet it remains unclear

Evaluating Fine-Tuning and Metrics for Neural Decompilation of Dart AOT Binaries

arXiv:2607.06125v1 Announce Type: cross Abstract: Neural decompilation is increasingly studied as a code-generation problem, yet its evaluation methodology remains underdeveloped for modern languages.

Finally can share that I have been testing GPT-5.6 early and oooo boy. It is an execution beast. So much so that I think 5.6 is the absolute…

model-releasesallie-k--miller--x

Finally can share that I have been testing GPT-5.6 early and oooo boy. It is an execution beast. So much so that I think 5.6 is the absolute wrong name considering how big of a leap this felt to me. T

FirstResearch: Auditable Question Formation for LLM Scientific Discovery Agents

arXiv:2607.05682v1 Announce Type: new Abstract: LLM systems for scientific discovery increasingly assist with ideation, literature synthesis, experiment planning, and report generation, but the first

From Pixels to Portraits: A Comprehensive Survey of Talking Head Generation Techniques and Applications

arXiv:2308.16041v2 Announce Type: replace Abstract: Talking head generation has progressed rapidly from landmark- and GAN-based facial animation to diffusion models, neural rendering, 3D-aware avatars

safetyarxiv-cs-cv

GaussFusion: Towards Multimodal 3D Gaussian Pretraining

arXiv:2607.05906v1 Announce Type: new Abstract: 3D Gaussian Splatting provides an explicit representation that jointly models geometry and appearance, serving as a scalable foundation for 3D represent

safetyarxiv-cs-cv

Applications

Ground3D-LMM: Fine-Grained 3D Point Grounding and Spatial Reasoning with LMM

arXiv:2607.05493v1 Announce Type: new Abstract: Natural-language queries about 3D environments become actionable when responses are verifiable and metric. Verifiability requires explicit grounding to

applicationsarxiv-cs-cv