Search: “context”

Autonomous Traffic Signal Optimization Using Digital Twin and Agentic AI for Real-Time Decision-Making

arXiv:2604.27753v1 Announce Type: new Abstract: This article outlines a new framework of traffic light optimization through a digital twin of the transport infrastructure, managed by agentic AI to ens

agentsarxiv-cs-ai

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Local Ai

Can Tabular Foundation Models Guide Exploration in Robot Policy Learning?

DGX agent

arXiv:2604.27667v1 Announce Type: cross Abstract: Policy optimization in high-dimensional continuous control for robotics remains a challenging problem. Predominant methods are inherently local and of

local-aiarxiv-cs-lg

1 May 2026

ClipTBP: Clip-Pair based Temporal Boundary Prediction with Boundary-Aware Learning for Moment Retrieval

arXiv:2604.27591v1 Announce Type: cross Abstract: Video moment retrieval is the task of retrieving specific segments of a video corresponding to a given text query. Recent studies have been conducted

Crab: A Semantics-Aware Checkpoint/Restore Runtime for Agent Sandboxes

arXiv:2604.28138v1 Announce Type: cross Abstract: Autonomous agents act through sandboxed containers and microVMs whose state spans filesystems, processes, and runtime artifacts. Checkpoint and restor

agentsarxiv-cs-ai

create_agent - how we build Deep Agents on the simplest harness primitive underlying all of the harness engineering, research, and API desig…

create_agent - how we build Deep Agents on the simplest harness primitive underlying all of the harness engineering, research, and API design in Deep Agents is a very simple primitive in LangChain cal

agentsharrison-chase--x

DeepWeightFlow: Re-Basined Flow Matching for Generating Neural Network Weights

arXiv:2601.05052v2 Announce Type: replace Abstract: Building efficient and effective generative models for neural network weights has been a research focus of significant interest that faces challenge

researcharxiv-cs-lg

Design Structure Matrix Modularization with Large Language Models

arXiv:2604.28018v1 Announce Type: cross Abstract: Design Structure Matrix (DSM) modularization, the task of partitioning system elements into cohesive modules, is a fundamental combinatorial challenge

Dreaming Across Towns: Semantic Rollout and Town-Adversarial Regularization for Zero-Shot Held-Out-Town Fixed-Route Driving in CARLA

arXiv:2604.27994v1 Announce Type: new Abstract: Learned driving agents often degrade when deployed in unseen environments. This paper studies a deliberately bounded instance of that problem in the CAR

safetyarxiv-cs-ro

Local Ai

Echo-{alpha}: Large Agentic Multimodal Reasoning Model for Ultrasound Interpretation

arXiv:2604.28011v1 Announce Type: new Abstract: Ultrasound interpretation requires both precise lesion localization and holistic clinical reasoning, yet existing methods typically excel at only one of

local-aiarxiv-cs-cv

Local Ai

ELiC: Efficient LiDAR Geometry Compression via Cross-Bit-depth Feature Propagation and Bag-of-Encoders

arXiv:2511.14070v3 Announce Type: replace-cross Abstract: Hierarchical LiDAR geometry compression encodes voxel occupancies from low to high bit-depths, yet prior methods treat each depth independentl

local-aiarxiv-cs-cv

Evaluating Epistemic Guardrails in AI Reading Assistants: A Behavioral Audit of a Minimal Prototype

arXiv:2604.27275v1 Announce Type: cross Abstract: Large language model (LLM) reading assistants are increasingly used in settings that require interpretation rather than simple retrieval. In these con

researcharxiv-cs-ai

Explainable Load Forecasting with Covariate-Informed Time Series Foundation Models

arXiv:2604.28149v1 Announce Type: new Abstract: Time Series Foundation Models (TSFMs) have recently emerged as general-purpose forecasting models and show considerable potential for applications in en

researcharxiv-cs-lg

Exploration Hacking: Can LLMs Learn to Resist RL Training?

arXiv:2604.28182v1 Announce Type: cross Abstract: Reinforcement learning (RL) has become essential to the post-training of large language models (LLMs) for reasoning, agentic capabilities and alignmen

safetyarxiv-cs-cl

Exploring Interaction Paradigms for LLM Agents in Scientific Visualization

arXiv:2604.27996v1 Announce Type: new Abstract: This paper examines how different types of large language model (LLM) agents perform on scientific visualization (SciVis) tasks, where users generate vi

Flattery in Motion: Benchmarking and Analyzing Sycophancy in Video-LLMs

arXiv:2506.07180v3 Announce Type: replace-cross Abstract: As video large language models (Video-LLMs) become increasingly integrated into real-world applications that demand grounded multimodal reason

From surveillance to signalling: escalation channels as environmental controls for agentic AI

arXiv:2510.05192v2 Announce Type: replace-cross Abstract: When AI agents operating with access to sensitive information encounter a conflict between completing an assigned task and following rules or

From Unstructured Recall to Schema-Grounded Memory: Reliable AI Memory via Iterative, Schema-Aware Extraction

arXiv:2604.27906v1 Announce Type: new Abstract: Persistent AI memory is often reduced to a retrieval problem: store prior interactions as text, embed them, and ask the model to recover relevant contex

Generate Your Talking Avatar from Video Reference

model-releasesarxiv-cs-cv

arXiv:2604.27918v1 Announce Type: new Abstract: Existing talking avatar methods typically adopt an image-to-video pipeline conditioned on a static reference image within the same scene as the target g

Graph-Based Biomarker Discovery and Interpretation for Alzheimer's Disease

arXiv:2411.18796v2 Announce Type: replace Abstract: Early diagnosis and discovery of therapeutic drug targets are crucial objectives for effective management of Alzheimer's Disease (AD). Current appro

researcharxiv-cs-lg

HATS: An Open data set Integrating Human Perception Applied to the Evaluation of Automatic Speech Recognition Metrics

arXiv:2604.27542v1 Announce Type: new Abstract: Conventionally, Automatic Speech Recognition (ASR) systems are evaluated on their ability to correctly recognize each word contained in a speech signal.

researcharxiv-cs-cl

HERMES++: Toward a Unified Driving World Model for 3D Scene Understanding and Generation

model-releasesarxiv-cs-cv

arXiv:2604.28196v1 Announce Type: new Abstract: Driving world models serve as a pivotal technology for autonomous driving by simulating environmental dynamics. However, existing approaches predominant

Learning from Disagreement: Clinician Overrides as Implicit Preference Signals for Clinical AI in Value-Based Care

arXiv:2604.28010v1 Announce Type: cross Abstract: We reframe clinician overrides of clinical AI recommendations as implicit preference data - the same signal structure exploited by reinforcement learn

most of the time, you want an agent loop to run uninterrupted. that's where the utility comes from! but some decisions shouldn't be delegate…

most of the time, you want an agent loop to run uninterrupted. that's where the utility comes from! but some decisions shouldn't be delegated to the agent. two situations come up consistently: 1/ befo

agentsharrison-chase--x

NanoKnow: How to Know What Your Language Model Knows

arXiv:2602.20122v2 Announce Type: replace-cross Abstract: How do large language models (LLMs) know what they know? Answering this question has been difficult because pre-training data is often a 'blac

NEW paper: Recursive Multi-Agent Systems

NEW paper: Recursive Multi-Agent Systems // Recursive Multi-Agent Systems // Great read for the weekend. (bookmark it) Multi-agent systems often pass full text messages between agents at every step. T

agentsdair-ai--x

Not All Memories Age the Same: Autodiscovery of Adaptive Decay in Knowledge Graphs

arXiv:2604.26970v1 Announce Type: cross Abstract: Knowledge graphs used for retrieval treat all facts as equally current. Existing temporal approaches apply uniform decay, using a single forgetting cu

researcharxiv-cs-ai

ObjectGraph: From Document Injection to Knowledge Traversal -- A Native File Format for the Agentic Era

arXiv:2604.27820v1 Announce Type: new Abstract: Every document format in existence was designed for a human reader moving linearly through text. Autonomous LLM agents do not read - they retrieve. This

Industry

ok its not the most important thing we've ever done but i find it more useful than it seems on the surface. check out pets in codex! (and tr…

Sam Altman highlights a feature called 'pets in Codex,' suggesting it's a practical tool within OpenAI's Codex that may seem minor but offers more utility than initially apparent. The post encourages

industrysam-altman--x

Tutorials

Omni-Attribute: Open-vocabulary Attribute Encoder for Visual Concept Personalization

arXiv:2512.10955v2 Announce Type: replace Abstract: Visual concept personalization aims to transfer only specific image attributes, such as identity, expression, lighting, and style, into unseen conte

tutorialsarxiv-cs-cv

On 5/5 @realDanFu and team will discuss DSV4’s hybrid attention and KV cache efficiency, should be a great session!

model-releasestogether-ai--x

On 5/5 @realDanFu and team will discuss DSV4’s hybrid attention and KV cache efficiency, should be a great session! Join us Tue 5/5: #DeepSeek-V4's hybrid attention + sparse MoE reduces KV cache up to

OpenAI o1 System Card

arXiv:2412.16720v2 Announce Type: replace Abstract: The o1 model series is trained with large-scale reinforcement learning to reason using chain of thought. These advanced reasoning capabilities provi

OpenClassGen: A Large-Scale Corpus of Real-World Python Classes for LLM Research

arXiv:2504.15564v3 Announce Type: replace-cross Abstract: Existing class-level code generation datasets are either synthetic (ClassEval: 100 classes) or insufficient in scale for modern training needs

OR-VSKC: Resolving Visual-Semantic Knowledge Conflicts in Operating Rooms with Synthetic Data-Guided Alignment

arXiv:2506.22500v2 Announce Type: replace-cross Abstract: Automated identification of surgical safety risks is critical for improving patient outcomes; however, Multimodal Large Language Models (MLLMs

Policy-Grounded Safety Evaluation of 20 Large Language Models

arXiv:2507.14719v2 Announce Type: replace Abstract: As large language models (LLMs) become increasingly integrated into real-world applications, scalable and rigorous safety evaluation is essential. T

Applications

Position-Aware Drafting for Inference Acceleration in LLM-Based Generative List-Wise Recommendation

arXiv:2604.27747v1 Announce Type: cross Abstract: Large language model (LLM)-based generative list-wise recommendation has advanced rapidly, but decoding remains sequential and thus latency-prone. To

applicationsarxiv-cs-ai

Tutorials

Reasoning over Object Descriptions Improves Coreference Resolution in Task-Based Dialogue Systems

arXiv:2604.27850v1 Announce Type: new Abstract: Task-based dialogue systems assist users in achieving specific goals, such as executing actions or retrieving information, through natural language inte

tutorialsarxiv-cs-cl

Applications

Reliable Answers for Recurring Questions: Boosting Text-to-SQL Accuracy with Template Constrained Decoding

arXiv:2604.28028v1 Announce Type: cross Abstract: Large language models (LLMs) have revolutionized Text-to-SQL generation, allowing users to query structured data using natural language with growing e

applicationsarxiv-cs-ai

RPC-Bench: A Fine-grained Benchmark for Research Paper Comprehension

arXiv:2601.14289v2 Announce Type: replace-cross Abstract: Understanding research papers remains challenging for foundation models due to specialized scientific discourse and complex figures and tables

RuC: HDL-Agnostic Rule Completion Benchmark Generation

arXiv:2604.27780v1 Announce Type: cross Abstract: Large Language Models (LLMs) have rapidly improved in performance across code-related tasks, making their integration into Register Transfer Level (RT

SASI: Leveraging Sub-Action Semantics for Robust Early Action Recognition in Human-Robot Interaction

arXiv:2604.27508v1 Announce Type: new Abstract: Understanding human actions is critical for advancing behavior analysis in human-robot interaction. Particularly in tasks that demand quick and proactiv

researcharxiv-cs-ro

Security Attack and Defense Strategies for Autonomous Agent Frameworks: A Layered Review with OpenClaw as a Case Study

arXiv:2604.27464v1 Announce Type: cross Abstract: Autonomous agent frameworks built upon large language models (LLMs) are evolving into complex, tool-integrated, and continuously operating systems, in

agentsarxiv-cs-ai

Industry

Securonix partners with AI SPERA to bring Criminal IP intelligence to ThreatQ

Cybersecurity company Securonix Inc. today announced a new partnership with cyberthreat intelligence company AI SPERA Inc. to deliver integrated threat intelligence enrichment through its ThreatQ Plat

industrysiliconangle

Self-Supervised Learning of Plant Image Representations

arXiv:2604.27538v1 Announce Type: new Abstract: Automated plant recognition plays a crucial role in biodiversity monitoring and conservation, yet current approaches rely heavily on supervised learning

researcharxiv-cs-cv

The TEA Nets framework combines AI and cognitive network science to model targets, events and actors in text

arXiv:2604.27673v1 Announce Type: new Abstract: We introduce Target-Event-Agent Networks (TEA Nets) as a computational framework to extract subjects (``Agents'), verbs (``Events'), and objects (``Targ

Theory Under Construction: Orchestrating Language Models for Research Software Where the Specification Evolves

arXiv:2604.27209v1 Announce Type: cross Abstract: Large language models can now generate substantial code and draft research text, but research-software projects require more than either artifact alon

Towards All-Day Perception for Off-Road Driving: A Large-Scale Multispectral Dataset and Comprehensive Benchmark

model-releasesarxiv-cs-cv

arXiv:2604.27499v1 Announce Type: new Abstract: Off-road nighttime autonomous driving suffers from unreliable visible-light perception, making infrared modality crucial for accurate freespace detectio

Local Ai

Training-Free Tunnel Defect Inspection and Engineering Interpretation via Visual Recalibration and Entity Reconstruction

arXiv:2604.27928v1 Announce Type: cross Abstract: Tunnel inspection requires outputs that can support defect localization, measurement, severity grading, and engineering documentation. Existing traini

local-aiarxiv-cs-ai

Applications

TwinGate: Stateful Defense against Decompositional Jailbreaks in Untraceable Traffic via Asymmetric Contrastive Learning

arXiv:2604.27861v1 Announce Type: cross Abstract: Decompositional jailbreaks pose a critical threat to large language models (LLMs) by allowing adversaries to fragment a malicious objective into a seq

applicationsarxiv-cs-cl