Search: “models”

arXiv:2607.02119v1 Announce Type: cross Abstract: While Large Multimodal Models excel in comprehension, high-throughput inference engines lack native support for multimodal generation. This is severe

hardwarearxiv-cs-ai

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Safety

Beyond Next-Token Prediction: An RLVR Proof of Concept for Tool-Use Agents on Atlassian Workflows

DGX agent

arXiv:2607.01465v1 Announce Type: new Abstract: Large language models are trained to predict the next token, not to act inside a specific API. In niche enterprise SaaS workflows -- where success means

safetyarxiv-cs-ai

3 Jul 2026

Beyond Pixel Diffs: Benchmarking Image Change Captioning for Web UI Visual Regression Testing

model-releasesarxiv-cs-cl

arXiv:2607.01728v1 Announce Type: cross Abstract: Visual regression testing (VRT) is a standard quality assurance step in modern software release pipelines. On every change, it re-renders user interfa

Agents

Beyond Supervised Clarification: Input Rewriting with LLMs for Dialogue Discourse Parsing

arXiv:2607.01964v1 Announce Type: new Abstract: Rewriting inputs to improve frozen downstream models has become a common strategy in modern NLP pipelines. Prior work on incremental dialogue discourse

agentsarxiv-cs-cl

Born Discrete, Made Smooth: Variational Formulation of Shallow Neural Networks

arXiv:2607.02003v1 Announce Type: cross Abstract: Although neural networks are remarkably effective, their underlying optimization principles remain theoretically elusive, often characterized by non-c

Boundary-Aware Quantization: Finite-Scale Decision Geometry of Neural Classifiers

arXiv:2607.01478v1 Announce Type: cross Abstract: We measured quantization-induced decision-boundary changes using local logit-margin radii, first-order boundary displacement, normal variation, slice-

Agents

CausalSteward: An Agentic Divide-Conquer-Combine Copilot for Causal Discovery

arXiv:2607.01936v1 Announce Type: cross Abstract: Learning causal models from high-dimensional data is a significant challenge, particularly in real-world settings where violations of core assumptions

agentsarxiv-cs-ai

CoFL-S: Spatially Queryable Sector Flow Fields for Local Language-Conditioned Navigation

arXiv:2607.02222v1 Announce Type: cross Abstract: Vision-Language Navigation has increasingly emphasized high-level instruction reasoning, memory, global map construction, and instruction decompositio

Collaborative Disagreement Resolution for Scalable Oversight

arXiv:2607.01251v1 Announce Type: cross Abstract: Debate, where AI agents argue opposing positions, has emerged as a key approach to scalable oversight. However, debate faces a fundamental tension: mo

Decoupling Code Complexity from Newcomer Participation: A Causal Study of AI Coding Agent Adoption in OSS

arXiv:2607.01810v1 Announce Type: cross Abstract: Open-source projects depend on a steady inflow of newcomers. A growing concern is that AI coding agents (tools such as Cursor and Claude Code that wri

Diverse Evidence, Better Forecasts: Multi-Agent Deliberation Under Information Asymmetry

arXiv:2607.01661v1 Announce Type: new Abstract: Multi-agent systems are increasingly used for forecasting future events, as deliberation among multiple LLMs is believed to improve reasoning and calibr

DL-VINS-Factory: A Modular Framework for Learned Visual Front-Ends in Visual-Inertial SLAM

model-releasesarxiv-cs-ro

arXiv:2607.01757v1 Announce Type: cross Abstract: Deep-learning features excel in visual matching, yet their practical value in tightly coupled visual-inertial SLAM (VI-SLAM) remains insufficiently ch

Safety

DRL-CLBA: A Clean Label Backdoor Attack for Speech Classification via DDPG Reinforcement Learning

arXiv:2607.01729v1 Announce Type: new Abstract: Deep learning models for speech classification are vulnerable to backdoor attacks, where malicious triggers cause misclassification at inference time. W

safetyarxiv-cs-ai

Tutorials

Enerzyme: A Framework for Efficient Training of Reactive Neural Network Potentials for Enzyme Catalysis with Application to Methyltransferases

arXiv:2607.01362v1 Announce Type: cross Abstract: Quantum mechanical (QM) cluster models provide an effective framework for mechanistic studies of enzymatic reactions but remain computationally demand

tutorialsarxiv-cs-lg

Enhancing Fitness Intelligence through Domain-Specific LLM Post-Training

arXiv:2607.02118v1 Announce Type: new Abstract: Scientific Fitness Coaching (SFC) is typically delivered by human professionals, making it costly and inaccessible to many. While recent advances in Lar

Evolutionary Feature Engineering for Structured Data

arXiv:2607.01548v1 Announce Type: cross Abstract: Large language models are increasingly used as open-ended search operators in evolutionary optimization. We introduce Evolutionary Feature Engineering

eXact-Prior Variational Autoencoder (X-VAE): Learning Data-Adaptive Gaussian Mixture Priors for Latent Distributions

arXiv:2607.01275v1 Announce Type: cross Abstract: Variational Autoencoders (VAEs) commonly assume a standard isotropic Gaussian prior over the latent space, an assumption that often fails to capture t

Expander Sparse Autoencoders: Parameter-Efficient Dictionaries for Mechanistic Interpretability

arXiv:2607.01799v1 Announce Type: cross Abstract: Sparse autoencoders (SAEs) decompose internal activations of neural networks into sparse linear combinations of learned features by fitting an overcom

Fourier Neural Operators for Rayleigh-Benard Convection

arXiv:2607.02088v1 Announce Type: new Abstract: We propose an improved Fourier Neural Operator (FNO) for modeling two-dimensional Rayleigh-Benard convection by predicting time increments instead of fu

researcharxiv-cs-lg

Frequency Shift Physics-Informed Extreme Learning Machine for Solving High-Frequency Partial Differential Equations

arXiv:2607.01694v1 Announce Type: new Abstract: Solving partial differential equations (PDEs) with high-frequency solutions remains a central challenge in physics-informed machine learning due to spec

GroundEval: A Deterministic Replacement for LLM-as-Judge in Stateful Agent Evaluation

arXiv:2606.22737v2 Announce Type: replace Abstract: Before letting an agent operate over real context, can you prove it used the right evidence? GroundEval turns that question into a deterministic tes

Has This Checkpoint Been Abliterated? A Two-Signal Audit and Its Failure Map

arXiv:2607.01854v1 Announce Type: cross Abstract: Can a platform tell, before deployment, whether an open-weight checkpoint has had its refusal mechanism stripped? Runtime guards cannot: they score ge

HERMES: A Multi-Granularity Labeling Substrate for Pre-training Data Mixtures

arXiv:2607.02266v1 Announce Type: cross Abstract: Most data-mixing methods assume the corpus has already been partitioned into groups, and the choice of those groups determines what a mixer can expres

Hidden Forgetting in Continual Multimodal Learning: When Accuracy Survives but Grounding Fails

arXiv:2607.02020v1 Announce Type: new Abstract: Multimodal large language models must continually adapt to evolving tasks and domains, yet standard continual learning metrics mainly measure whether ol

HNSW with Accuracy Guarantees Using Graph Spanners -- A Technical Report

model-releasesarxiv-cs-cl

arXiv:2607.02338v1 Announce Type: cross Abstract: Hierarchical Navigable Small World (HNSW) graphs serve as the industry standard due to their logarithmic complexity and strong empirical performance.

HULAT2 at MER-TRANS 2026: Governed Multi-Agent Simplification for Spanish Easy-to-Read Generation

model-releasesarxiv-cs-cl

arXiv:2607.02381v1 Announce Type: new Abstract: This paper describes the participation of HULAT2-UC3M in the Spanish track of MER-TRANS 2026, a shared task on multilingual Easy-to-Read translation. Th

IonSense-QKG: A Quantum-Readiness Metadata Framework for Lithium-Ion Battery Dataset Discovery

arXiv:2607.01286v1 Announce Type: new Abstract: Public lithium-ion battery datasets are increasingly used for state-of-health estimation, remaining-useful-life prediction, anomaly detection, electroch

Local Ai

Learning to Localize Reference Trajectories in Image-Space for Visual Navigation

arXiv:2602.18803v2 Announce Type: replace Abstract: We present LoTIS, a model for visual navigation that provides robot-agnostic image-space guidance by localizing a reference RGB trajectory in the ro

local-aiarxiv-cs-ro

Tutorials

LEFT: Learnable Fusion of Tri-view Tokens for Unsupervised Time Series Anomaly Detection

arXiv:2602.08638v2 Announce Type: replace-cross Abstract: As a fundamental data mining task, unsupervised time series anomaly detection (TSAD) aims to build a model for identifying abnormal timestamps

tutorialsarxiv-cs-ai

Agents

Lynx: Progressive Speculative Quantization for accelerating KV Transfer in Long-Context Inference

arXiv:2607.01831v1 Announce Type: cross Abstract: Long-context inference is increasingly common in large language model (LLM) serving, driven by retrieval-augmented generation and agentic systems. In

agentsarxiv-cs-lg

Mastermind: Strategy-grounded Learning for Repository-Scale Vulnerability Reproduction

arXiv:2607.01764v1 Announce Type: new Abstract: Repository-level vulnerability reproduction is a demanding software engineering (SE) task: an agent must inspect a codebase, infer the input grammar tha

MedRepBench: A Comprehensive Benchmark for Medical Report Interpretation

arXiv:2508.16674v2 Announce Type: replace-cross Abstract: Medical report understanding from real-world document images is essential for generating patient-facing explanations and enabling structured i

Applications

Motion-Focused Latent Action Enables Cross-Embodiment VLA Training from Human EgoVideos

arXiv:2606.18955v2 Announce Type: replace-cross Abstract: Training generalist Vision-Language-Action(VLA) models typically requires massive, diverse robotic datasets with high-fidelity action annotati

applicationsarxiv-cs-ro

Safety

Multi-Objective Exploration and Preference Optimization via Mutual Information

arXiv:2607.01392v1 Announce Type: new Abstract: Aligning large language models with diverse and heterogeneous human values requires multi-objective alignment methods to effectively trade off conflicti

safetyarxiv-cs-cl

Multilingual Prompt Localization for Agent-as-a-Judge: Language and Backbone Sensitivity in Requirement-Level Evaluation

arXiv:2604.04532v2 Announce Type: replace-cross Abstract: Evaluation language is typically treated as a fixed English default in agentic code benchmarks, yet we show that changing the judge's language

NEUROSYMLAND: Neuro-Symbolic Landing-Site Assessment for Robust and Edge-Deployable UAV Autonomy

model-releasesarxiv-cs-ro

arXiv:2607.02277v1 Announce Type: new Abstract: Safe landing-site assessment in unstructured environments remains a key challenge for autonomous UAV deployment, as vision-only learning approaches ofte

Office Comprehension Benchmark

arXiv:2607.01245v1 Announce Type: cross Abstract: We introduce Office Comprehension Bench (OCB), the first public benchmark to jointly evaluate LLM systems on Word, Excel, and PowerPoint comprehension

OrbitQuant: Data-Agnostic Quantization for Image and Video Diffusion Transformers

arXiv:2607.02461v1 Announce Type: cross Abstract: Diffusion transformers (DiTs) achieve state-of-the-art image and video generation, but their multi-step sampling and growing parameter count make infe

Path-level Hindsight Instructions for Semantic Exploration in Vision-Language Navigation

arXiv:2607.01754v1 Announce Type: new Abstract: On-policy exploration is a crucial component for training robust Vision-Language Navigation agents, as it exposes the policy to a broader state distribu

Applications

Profit-Based Counterfactual Explanations for Product Improvement: A Case Study of Manga Sales in Japan

arXiv:2607.01610v1 Announce Type: new Abstract: Counterfactual explanation (CE) is widely used to enhance the interpretability of machine learning models and support data-driven decision-making based

applicationsarxiv-cs-ai

ReContext: Recursive Evidence Replay as LLM Harness for Long-Context Reasoning

arXiv:2607.02509v1 Announce Type: new Abstract: Understanding and reasoning over long contexts has become a key requirement for deploying large language models (LLMs) in realistic applications. Althou

RuleChef: Grounding LLM Task Knowledge in Human-Editable Rules

arXiv:2607.01293v1 Announce Type: new Abstract: We present RuleChef, a framework that uses large language models (LLMs) to generate executable rules for NLP tasks such as text classification, Named En

researcharxiv-cs-cl

Scaling to Multimodal and Multichannel Heart Sound Classification with Synthetic and Augmented Biosignals

arXiv:2509.11606v4 Announce Type: replace-cross Abstract: Cardiovascular diseases (CVDs) are the leading cause of death worldwide, accounting for approximately 17.9 million deaths each year. Early det

researcharxiv-cs-lg

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion

arXiv:2607.01777v1 Announce Type: cross Abstract: Radio frequency (RF) maps provide a compact representation of multipath propagation characteristics and are fundamental to channel modeling, coverage

Self-Gating Attention for Efficient Time Series Forecasting

arXiv:2607.02344v1 Announce Type: cross Abstract: Transformer architectures have shown strong potential in time series forecasting, where multi-head self-attention is widely used to capture temporal d

SimWorlds: A Multi-Agent System for Dynamic 3D Scene Creation

arXiv:2607.01766v1 Announce Type: new Abstract: LLM agents are increasingly used to translate natural language into 3D scenes in a procedural way, but existing systems focus on static output. Dynamic

SPOT: Spatio-Temporal Obstacle-free Trajectory Planning for UAVs in Unknown Dynamic Environments

model-releasesarxiv-cs-ro

arXiv:2602.01189v3 Announce Type: replace Abstract: We address the problem of reactive motion planning for quadrotors operating in unknown environments with dynamic obstacles. Our approach leverages a

Steerability via constraints: a substrate for scalable oversight of coding agents

arXiv:2607.02389v1 Announce Type: new Abstract: Coding agents are capable; human oversight is the bottleneck. Unconstrained agents introduce security risks, erode codebase scalability, and make human