Search: “models”

Sam Altman: “Concentration of power with AI is a terrifying thing.” 'A lot of the talk about safety concerns is well-founded, and then a lot…

Sam Altman: “Concentration of power with AI is a terrifying thing.” 'A lot of the talk about safety concerns is well-founded, and then a lot of it is about people that just really, even if it's slight

safetyclem-delangue--x

Agents

SetGo: Metadata Readiness for Scientific AI Datasets

DGX agent

arXiv:2607.22677v1 Announce Type: cross Abstract: Scientific datasets intended for AI use require both computational readiness for model training and metadata readiness for discovery, sharing, and reu

agentsarxiv-cs-ai

28 Jul 2026

Local Ai

Share No More Than the Request Requires: Federated Disclosure for Perspective-Aware AI

arXiv:2607.22953v1 Announce Type: new Abstract: Modern AI systems bring societal risks such as mass surveillance, extreme concentrations of power, and loss of user autonomy---calling into question a m

local-aiarxiv-cs-ai

Sparse Autoencoders Encode Both Concepts and Functions: The Downstream Geometry of Feature Effects

arXiv:2607.24645v1 Announce Type: cross Abstract: The wide-scale use of sparse autoencoders (SAEs) as interpretability tools is limited by inconsistent links between SAE features and model behavior. F

researcharxiv-cs-ai

Agents

SpecBox: Speculative Sandbox Scheduling for Efficient LLM Agent Serving

arXiv:2607.23933v1 Announce Type: cross Abstract: As LLM agents increasingly rely on the Model Context Protocol (MCP) to invoke isolated external sandboxes, disaggregated sandbox deployment introduces

agentsarxiv-cs-ai

StAR: Segment Anything Reasoner

arXiv:2603.14382v2 Announce Type: replace Abstract: As AI systems are being integrated more rapidly into diverse and complex real-world environments, the ability to perform holistic reasoning over an

SwitchBraidNet: Quantisation-Aware Lightweight Architecture for Hybrid Brain-Computer Interface

arXiv:2606.18816v2 Announce Type: replace-cross Abstract: Hybrid brain-computer interfaces (BCIs) that integrate motor imagery (MI) and steady-state visual evoked potentials (SSVEP) provide high-dimen

researcharxiv-cs-ai

TLRNet: Estimating Individual Treatment Effect based on Local Information and Single Learner Structure

arXiv:2607.22762v1 Announce Type: cross Abstract: Causal inference has become a central issue across various fields, including computer science, statistics, economics, education, healthcare, and medic

Applications

Traceable LLM Reasoning for Fake-Order Fraud Detection

arXiv:2607.23075v1 Announce Type: cross Abstract: Detecting fake-order fraud at scale remains a critical challenge for large online-to-offline (O2O) service platforms, as existing approaches often rel

applicationsarxiv-cs-ai

Transfer learning for conflict and duplicate detection in software requirement pairs

arXiv:2301.03709v3 Announce Type: replace-cross Abstract: Consistent and holistic expression of software requirements is important for the success of software projects. In this study, we aim to enhanc

Try Once, Then Optimal: De-Redundified Procedure Memory for Cross-Episode Exploration Amortization

model-releasesarxiv-cs-ro

arXiv:2607.23702v1 Announce Type: new Abstract: Manipulating objects with hidden internal state, such as a latched microwave, forces a robot to probe before it can act. Yet a robot that has solved an

Using Reinforcement Learning to Optimize the Global and Local Crossing Number

arXiv:2509.06108v3 Announce Type: replace-cross Abstract: Graph drawing concerns the algorithmic visualization of graphs. A good drawing of a graph is easy to read and facilitates solving tasks on the

Variational-Ising-Attention (VIA):TailoredAttentionMattersfor Science

arXiv:2607.23634v1 Announce Type: cross Abstract: Attention enables context modeling via query-key scoring with softmax normalization. Driven by industrial long-context demands, mainstream research ha

researcharxiv-cs-ai

VL-LN Bench: Towards Long-horizon Goal-oriented Navigation with Active Dialogs

model-releasesarxiv-cs-ro

arXiv:2512.22342v5 Announce Type: replace Abstract: In most existing embodied navigation tasks, instructions are well-defined and unambiguous, such as instruction following and object searching. Under

Wrong Design Intent Is Worse Than None: A Derangement-Control Diagnosis of Header Conditioning in CAD Program Completion

arXiv:2607.23191v1 Announce Type: new Abstract: Fine-tuned code LLMs can be conditioned on a lightweight design-intent header to steer parametric CAD generation, but whether the model actually reads t

XMatchAD: A Cross-Modal Matching Perspective on Reconstruction-based Anomaly Detection

arXiv:2607.23658v1 Announce Type: new Abstract: The remarkable success of reconstruction-based methods in Unsupervised Anomaly Detection (UAD) lies in their ability to identify and localize anomalies

XMix: Combating Extremely Noisy Labels via Local Smoothness in Self-Supervised Feature Space

arXiv:2607.23865v1 Announce Type: new Abstract: Supervised deep learning models rely on large, accurately labeled datasets, yet noisy annotations are often unavoidable and can severely degrade perform

A Comparative Benchmark of Federated Learning Strategies for Mortality Prediction on Heterogeneous and Imbalanced Clinical Data

arXiv:2509.10517v3 Announce Type: replace Abstract: Machine learning can predict in-hospital mortality, but data privacy and the statistical heterogeneity of clinical data hamper its use. Federated Le

Applications

A Robust Pipeline for Differentially Private Federated Learning on Imbalanced Clinical Data using SMOTETomek and FedProx

arXiv:2508.10017v2 Announce Type: replace-cross Abstract: Federated Learning (FL) presents a groundbreaking approach for collaborative health research, allowing model training on decentralized data wh

applicationsarxiv-cs-lg

Tutorials

Alleviating Regional Shortcuts for Few-Shot Class-Incremental Learning

arXiv:2607.22072v1 Announce Type: new Abstract: Few-shot class-incremental learning (FSCIL) aims to incrementally learn novel classes with only a few samples while avoiding forgetting base classes. Ho

tutorialsarxiv-cs-cv

Announcing general availability of SAP Business Data Cloud Connect for BigQuery

model-releasesgoogle-cloud-ai

Traditional data replication techniques often struggle to deliver the data freshness that modern workflows require. To help organizations overcome this challenge, SAP and Google Cloud are announcing t

as the progenitor of the agent lab thesis which got the evals/routing/interactivity/ROI focus right i gotta say the biggest argument against…

as the progenitor of the agent lab thesis which got the evals/routing/interactivity/ROI focus right i gotta say the biggest argument against myself is that Claude Code got accidentally 'open sourced'

model-releasesswyx--x

b10142

model-releasesllama-cpp-releases

mtmd: Add Vision Support for Minimax-M3 (#25113) Add preliminary MiniMax-M3 support Text-only port that re-uses existing components: MiniMax-M2 style GQA with per-head QK-norm and partial rotary, Deep

btw anthropic's internal document on this literally said 'we don't want it to be known that we are working on this.” it was called project p…

model-releasesgary-marcus--x

btw anthropic's internal document on this literally said 'we don't want it to be known that we are working on this.” it was called project panama. here's exactly what happened: 1: anthropic concluded

Class-Balanced Softmax: A Bayes Theory-Based Method for Long-Tailed Recognition

arXiv:2607.22258v1 Announce Type: cross Abstract: Deep learning models using traditional softmax classifiers have achieved remarkable success in various classification tasks. However, their performanc

researcharxiv-cs-cv

CommandLM: Data driven behavior level descriptor for ego vehicles

arXiv:2607.22078v1 Announce Type: new Abstract: As autonomous driving systems move toward real-world deployment, interpretable, behavior-level decision-making is essential for safety, trust, and regul

safetyarxiv-cs-cv

Agents

Conformal Constraint Tightening for Chance-Constrained Motion Planning with Unknown Dynamics

arXiv:2607.22409v1 Announce Type: new Abstract: Motion planning algorithms compute control sequences that drive autonomous robots to goal regions while avoiding unsafe states. Existing methods, from s

agentsarxiv-cs-ro

DBA-Bench: A Production-Fidelity Benchmark for LLM-Based Database Operations Agents

model-releasesarxiv-cs-cl

arXiv:2607.22165v1 Announce Type: cross Abstract: LLM-based database agents show promise, but differing task scopes, testbeds, and metrics hinder comparison. We identify four gaps between evaluation a

Energy Manifold Natural Gradient Descent: Riemannian Optimization for Neural PDE Solvers

arXiv:2607.22004v1 Announce Type: new Abstract: Energy natural gradient descent (ENGD) aligns parameter updates with the curvature of an underlying function-space energy, but existing formulations ass

Evolution-Aware MSA Reasoning for Subsampling via Factor Graphs

arXiv:2607.22314v1 Announce Type: new Abstract: Multiple Sequence Alignments (MSAs) provide protein language models with explicit evolutionary context, but their large depth makes subsampling unavoida

GLI-AL: A Multi-Modal Glioma MRI Label Resource with Unified Anatomy-Lesion Labels

arXiv:2607.22135v1 Announce Type: new Abstract: Existing BraTS-GLI datasets provide a widely used benchmark for adult glioma MRI segmentation, but their task definition focuses on tumor subregions and

Great technical paper from Google. Great read on why context beats scale for agents working against unfamiliar APIs. (bookmark it) GPU kerne…

Great technical paper from Google. Great read on why context beats scale for agents working against unfamiliar APIs. (bookmark it) GPU kernel optimization has KernelBench to hillclimb on. TPUs had not

model-releasesdair-ai--x

Interior interpretability with attention rollout: contraction and propagation profiles in Transformers

arXiv:2607.22367v1 Announce Type: new Abstract: Feature-attribution methods assign scores relating input variables to a model's output, but do not by themselves characterize how explicitly defined int

Khondo: A Multimodal Benchmark for Document Packet Splitting of Bangla Forms

model-releasesarxiv-cs-cl

arXiv:2607.21780v1 Announce Type: new Abstract: Document packets, multiple documents concatenated into a single file, are common in government and administrative workflows, yet splitting them into the

Latent PDE mapping for efficient physics-informed learning across geometries with limited data

arXiv:2607.22215v1 Announce Type: new Abstract: In this study, we introduce latent PDE mapping, a broadly applicable physics-informed learning technique designed to enable efficient geometric generali

LayoutLite: Token-Level Implicit Layout Analysis for Efficient Document OCR

arXiv:2607.22200v1 Announce Type: new Abstract: End-to-end OCR systems based on vision-language models have achieved strong performance in complex document OCR, but their efficiency is limited by the

safetyarxiv-cs-cv

love this frame. calls to mind the role of the hippocampus in human navigation (via place cells and grid cells), and how navigation is, in a…

model-releasesyohei-nakajima--x

love this frame. calls to mind the role of the hippocampus in human navigation (via place cells and grid cells), and how navigation is, in a sense, what makes agents *agents* vs plain old LLM calls in

Nifer is insane. 700t/s with Qwen 3.6 35B (no thinking). Purpose build for RTX5090. Full 250k context too.

model-releasesr-localllama

I just managed to get it running on windows and this thing is fucking insane. I get around 550-720t/s depending on task at hand. Previously to get to such numbers i would have to do batching and agent

On Improving Faithfulness of Podcasts from Documents

arXiv:2607.21961v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to generate long-form conversational content such as podcasts from textual sources. While these syste

researcharxiv-cs-cl

Operator-Informed Gaussian Processes for Complex Helmholtz Wavefields: From Synthetic Benchmarks to In Vivo Brain Elastography

arXiv:2607.14193v2 Announce Type: replace-cross Abstract: The Helmholtz equation governs time-harmonic wave propagation, and in dissipative media a complex modulus renders its squared wavenumber kappa

Optimal Transport Image Representation and Deep Covariance Alignment (CORAL) for Control Valve Stiction Detection

arXiv:2607.22486v1 Announce Type: new Abstract: Control valve stiction is a common cause of unwanted oscillations and poor control-loop performance in industrial processes. Data-driven methods can aut

Parameter-free Adaptive Sparse Attention via Compression-Based Content Selection

arXiv:2607.21752v1 Announce Type: new Abstract: Data-adaptive sparse attention masks substantially outperform fixed patterns (e.g., BigBird and Longformer) and can even exceed dense attention on long

Probing Latent Colombian Identity Inferences in Qwen2.5-7B with Natural Language Autoencoders

arXiv:2607.21774v1 Announce Type: new Abstract: Large language models may infer demographic attributes from subtle linguistic cues even when those attributes are not explicitly stated. This pilot stud

safetyarxiv-cs-cl

Re-FORC: Adaptive Reward Prediction for Efficient Chain-of-Thought Reasoning

arXiv:2511.02130v2 Announce Type: replace-cross Abstract: We propose Re-FORC, an adaptive reward prediction method that, given a query, enables prediction of the expected future rewards as a function

Risk-Routed Implicit Boundary Refinement for Robust Ultrasound Image Segmentation

arXiv:2607.21787v1 Announce Type: new Abstract: Medical ultrasound (US) image segmentation faces significant challenges due to speckle noise, low-contrast boundaries, acoustic shadowing, and acquisiti

SCOPE and SCION: A Benchmark and an Auditable Reference Pipeline for Schema Induction and Fusion from Text

arXiv:2607.21610v1 Announce Type: cross Abstract: Schema graphs are an upstream bottleneck of schema-grounded information extraction and knowledge graph construction, yet most extraction systems assum

Spectral Flow Certificates for Depth-Aware Long-Range Propagation in Graph Neural Networks

arXiv:2607.21607v1 Announce Type: cross Abstract: Graph Neural Networks propagate information through local message passing, but the graph topologies themselves can silently prevent any amount of trai

Synthetic Speech, Real Signal: Paralinguistic Preservation and Cross-Lingual Augmentation via Voice Cloning

arXiv:2607.22304v1 Announce Type: new Abstract: Synthetic data augmentation in speech is common practice for linguistic tasks like ASR, but has seen far less work for paralinguistic ones, especially c