All entries

A Multi-Agent Human-LLM Collaborative Framework for Closed-Loop Scientific Literature Summarization

arXiv:2604.01452v2 Announce Type: replace Abstract: Scientific discovery is slowed by fragmented literature that requires excessive human effort to gather, analyze, and understand. AI tools, including

Content type

All Blog X Post Paper YouTube Reddit GitHub

Tools

A privacy gate on your Mac detects PII before it leaves your device. Choose to run that step locally, send the file to the cloud, or skip en…

DGX agent

A privacy gate on your Mac detects PII before it leaves your device. Choose to run that step locally, send the file to the cloud, or skip entirely. We are open-sourcing the classifier today. Read the

toolsperplexity--x

1 Sept 2026

A research agent is only as good as the search layer behind it! I built a Deep Research Agent using LangChain Deep Agents with a search-firs…

A research agent is only as good as the search layer behind it! I built a Deep Research Agent using LangChain Deep Agents with a search-first architecture designed around grounded, source-backed resea

agentsharrison-chase--x

A rigor-matched audit of periodic-step layer skipping for efficient llm inference: conflayers versus swift, with a supplemental analysis of trained routing alternatives

arXiv:2608.28846v1 Announce Type: cross Abstract: Layer-skipping methods for efficient LLM inference decide, at some granularity, which transformer layers to execute for a given input. We present a ri

researcharxiv-cs-ai

A Simple Method to Enhance Pre-trained Language Models with Speech Tokens for Classification

arXiv:2512.07571v3 Announce Type: replace Abstract: This paper presents a simple method that allows to easily enhance textual pre-trained large language models with speech information, when fine-tuned

researcharxiv-cs-cl

Local Ai

A Simple Transformer Pipeline for Full-Key Side-Channel Attacks on Uncropped Datasets

arXiv:2608.30105v1 Announce Type: cross Abstract: Deep learning-based side-channel analysis has historically focused on single-byte targets and manually cropped traces, which risks discarding exploita

local-aiarxiv-cs-lg

A Sliding Window Filter on the Galilean Group for Consistent Aided Inertial Navigation with Unknown Measurement Delays

arXiv:2608.29514v1 Announce Type: new Abstract: We study aided inertial navigation when the aiding sensor measurements are subject to an unknown constant delay. The goal is to estimate the delay and n

researcharxiv-cs-ro

A Spectral Identifiability Threshold for Dissipative Rate Recovery from Truncated Liouvillian Spectra

arXiv:2608.29302v1 Announce Type: new Abstract: Open quantum systems lose energy and phase coherence through different dissipative processes, but these processes can produce overlapping dynamical sign

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

model-releasesarxiv-cs-cv

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 Target-Centric Survey of Quantization-Aware Training

arXiv:2608.29667v1 Announce Type: new Abstract: The rapid development of LLMs incurs prohibitive memory footprints and intensive computational demands. Quantization-Aware Training (QAT) techniques hav

A Tensor Variational Formulation of Gradient Energy Total Variation

arXiv:2608.29172v1 Announce Type: new Abstract: We present a novel variational approach to a tensor-based total variation formulation which is called gradient energy total variation, GETV. We introduc

researcharxiv-cs-cv

A Unified Perspective on Conformal Prediction and Wasserstein Distributionally Robust Optimization for Uncertainty Quantification

arXiv:2608.29789v1 Announce Type: cross Abstract: Uncertainty quantification from finite data is central to machine learning, optimization, and automation systems, where decisions must remain reliable

A Unifying Perspective on Language Model Representations: From Filler-Role Structure to Mechanistic Interpretability

arXiv:2608.29034v1 Announce Type: cross Abstract: A wide range of methods have been proposed for interpreting language models, delivering important insights into their inner workings. However, differe

researcharxiv-cs-ai

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

Local Ai

A very confusing report from Puget Systems

Just to name a few: running Qwen3 8B on a 32GB GPU running Qwen3.6-27B Q4_K_M on 2 x R9700 quote: 'each prompt was sized at 500 input and 500 output tokens' for a full system that costs $18,775?? I do

local-air-localllama

A Visual Question Answering Model to Automate Nondestructive Evaluation Image Analysis

arXiv:2608.29408v1 Announce Type: new Abstract: This study introduces a Visual Question Answering model designed specifically for nondestructive evaluation applications. VQA models allow inspectors to

researcharxiv-cs-cv

Applications

A Zero-shot Generalized Graph Anomaly Detection Framework via Node Reconstruction

arXiv:2606.12673v2 Announce Type: replace-cross Abstract: Cross-domain graph anomaly detection (GAD) aims to identify abnormal nodes in unseen target graphs, showing strong potential in real-world app

applicationsarxiv-cs-ai

Local Ai

A^2Agent: Action-Aware Reinforcement Learning for Repository-Level Code Localization Agents

arXiv:2608.29831v1 Announce Type: new Abstract: Localizing issue-relevant code regions is a critical step in automated software engineering. However, due to their reliance on sparse trajectory-level s

local-aiarxiv-cs-cl

Accelerate Vector Diffusion Maps by Landmarks

arXiv:2603.21247v2 Announce Type: replace-cross Abstract: We propose a landmark-constrained algorithm, LA-VDM (Landmark Accelerated Vector Diffusion Maps), to accelerate the Vector Diffusion Maps (VDM

Accelerating Unified Multimodal Models with Core-Expansion Routing and Unified Computation Scheduling

arXiv:2608.29291v1 Announce Type: new Abstract: Unified multimodal models jointly support understanding and generation, but incur substantial redundant computation across tokens, layers, and generatio

Tutorials

Acoustically Grounded Cost Learning for Open-Vocabulary Audio-Visual Semantic Segmentation

arXiv:2608.29121v1 Announce Type: new Abstract: Open-Vocabulary Audio-Visual Semantic Segmentation (OV-AVSS) aims to perform pixel-level segmentation of sound-emitting objects from an open set of cate

tutorialsarxiv-cs-cv

AcrossWAM1.0:A Modular Latent World-Action Stack for Compact Robot Policies

arXiv:2608.29937v1 Announce Type: new Abstract: Latent world-action models avoid rendering future pixels by predicting an action-relevant visual subgoal in feature space. LaWAM established this formul

'Act Like a 5th Grader' is Not Enough: Bounding Knowledge in LLM-Based User Simulators

arXiv:2608.30033v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to simulate human behavior but frequently fail to exhibit realistic cognitive constraints, sufferin

ACTD: Anchor-Based Cross-Tokenizer Distillation with Residual Regularization

arXiv:2608.29662v1 Announce Type: new Abstract: Knowledge distillation effectively transfers reasoning capabilities from large language models to lightweight student models. To enable knowledge transf

safetyarxiv-cs-cl

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

AdaFuse: Adaptive Ensemble Decoding with Test-Time Scaling for LLMs

arXiv:2601.06022v2 Announce Type: replace-cross Abstract: Large language models (LLMs) exhibit complementary strengths arising from differences in pretraining data, model architectures, and decoding b

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

AdaptAV: Continuous Adaption of Vision Models for Autonomous Vehicles Using Cloud-based Oracle

arXiv:2608.28673v1 Announce Type: new Abstract: Deploying vision perception models in autonomous vehicles requires that we prioritize inference speeds, resulting in a model with shallower architecture

agentsarxiv-cs-cv

Adaptive Doubly Robust Off-Policy Evaluation for Ranking Policies under Diverse User Behavior

arXiv:2608.29600v1 Announce Type: new Abstract: Off-policy evaluation (OPE) of ranking policies is challenging be- cause selecting and ordering multiple items from a candidate set makes the number of

safetyarxiv-cs-lg

Adaptive Multi-Branching for Shallow Decision Tree Induction

arXiv:2608.29262v1 Announce Type: cross Abstract: Decision trees are attractive for tabular prediction tasks because each prediction follows an interpretable sequence of feature-threshold tests. Under

researcharxiv-cs-ai

Adaptive teachers for amortized samplers

arXiv:2410.01432v3 Announce Type: replace Abstract: Amortized inference is the task of training a parametric model, such as a neural network, to approximate a distribution with a given unnormalized de

safetyarxiv-cs-lg

Applications

AdapToPASS: Ambiguity-aware Adaptive Spherical Transformer for Panoramic Semantic Segmentation

arXiv:2608.29081v1 Announce Type: new Abstract: Spherical Transformers have emerged as a promising framework for panoramic semantic segmentation (PASS) by operating directly on spherical geometry and

applicationsarxiv-cs-cv

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

model-releasesarxiv-cs-lg

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

model-releasesarxiv-cs-cv

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,

Adversarial Online Classification with a Preview

arXiv:2608.29503v1 Announce Type: new Abstract: Worst-case online classification is governed by sequential complexity, such as Littlestone dimension, and can be impossible even for statistically simpl

Adversarial Trust Poisoning in Vehicular Collaborative Perception

arXiv:2605.22122v2 Announce Type: replace-cross Abstract: Collaborative perception (CP) enables connected and autonomous vehicles to share sensor data and jointly reason about their environment. To de

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

Agent-Based Model Framework for the North Carolina Modeling Infectious Diseases Program (NC MInD ABM) Overview, Design Concepts, and Details Protocol

arXiv:2202.06853v2 Announce Type: cross Abstract: To help facilitate a variety of simulations related to healthcare facilities in North Carolina, we have developed an agent-based model (ABM) to accura

Agent cost management is about more than the model

Every LLM call your application makes costs money, and agentic applications make a lot of LLM calls. Arize AX now ships a Cost Agent that reads traces, ranks spend, and opens a pull request with the f

agentsarize-ai

Agent Zero Memory: Provenance-Aware Long-Term Memory for LLM Agents

arXiv:2608.29606v1 Announce Type: new Abstract: Large language model (LLM) agents need durable, faithful memory of everything a user or organization has said and stored, yet most memory systems commit

agentsarxiv-cs-cl

Agent2UCB: Agentic System for Generative Engine Optimization

arXiv:2608.29063v1 Announce Type: new Abstract: Large language model driven search engines such as Google AI Overviews and Perplexity have created new opportunities for Generative Engine Optimization

Hardware

Agentic AI is fundamentally reshaping cybersecurity requirements. The industry needs security designed into the entire AI stack, starting wi…

Agentic AI is fundamentally reshaping cybersecurity requirements. The industry needs security designed into the entire AI stack, starting with the silicon itself and not added as an afterthought. Thor

hardwareelon-musk--x

Agentic AI uncovers conserved cross-tissue protein co-abundance programs inaccessible to single-dataset analysis

arXiv:2608.28990v1 Announce Type: new Abstract: Protein co-abundance clusters preserved across tissues can reveal shared disease mechanisms and candidate therapeutic targets, particularly when protein

AgenticRag-R1: Agentic Reinforcement Learning with Stack Memory for Multi-Step Reasoning, Retrieval and Memorizing

arXiv:2608.29622v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) improves the factuality of large language models (LLMs), yet existing RAG systems often struggle with complex, mu

AgentLogs: A Dataset for Opening the Black Box of GitHub's Cloud Agent

arXiv:2608.29204v1 Announce Type: cross Abstract: Generative AI-based software engineering agents are becoming routine contributors to real-world software projects. On GitHub, developers can assign ta

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

Agents in the Large: Perception-Centered Architecture for Persistent Agents

arXiv:2608.30478v1 Announce Type: new Abstract: Cognitive language agents have achieved substantial progress by equipping language models with memory, tools, and decision-making procedures, enabling a

agentsarxiv-cs-cl