Search: “model-releases”

DuoMem: Towards Capable On-Device Memory Agents via Dual-Space Distillation

arXiv:2606.29961v1 Announce Type: cross Abstract: Large Language Model (LLM)-based agents can solve complex procedural tasks by interacting with environments over multiple turns, but this ability typi

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Dynamic Parsing and Updating Natural Language Specification using VLMs for Robust Vision-Language Tracking

DGX agent

arXiv:2606.29357v1 Announce Type: cross Abstract: Vision-language tracking guided by natural language specifications leverages high-level semantic cues of target objects to substantially boost trackin

model-releasesarxiv-cs-ai

30 Jun 2026

Dynamo: Dynamic Skill-Tool Evolution for Vision-Language Agents

arXiv:2606.30185v1 Announce Type: new Abstract: Improving vision-language models (VLMs) on visual reasoning typically requires retraining or hand-designed prompts and tools. We present Dynamo, a train

Earlier this month, the City of Starbase was excited to support residents, local fishermen, @SpaceX volunteers, and @SeaTurtleInc in rescuin…

model-releaseselon-musk--x

Earlier this month, the City of Starbase was excited to support residents, local fishermen, @SpaceX volunteers, and @SeaTurtleInc in rescuing 266-lb loggerhead Arlen from Boca Chica Beach jetties. She

Early Cue Precision Shapes Visual Shortcut Learning in Controlled Cue-Manipulation Benchmarks

arXiv:2606.30344v1 Announce Type: cross Abstract: Visual classifiers can achieve high matched-distribution accuracy while relying on low-level cues that fail under conflict or suppression. We test whe

Early Estimation of Language to Latent Alignment in Diffusion Models

arXiv:2512.08505v2 Announce Type: replace Abstract: Conditional diffusion models frequently suffer from language-image misalignments. Due to the ambiguity of intermediate noise corrupted latents, asse

Early Warning Signals for OpenVLA Failure under Visual Distribution Shift

arXiv:2606.29699v1 Announce Type: cross Abstract: Vision Language Action models combine perception, language grounding, and control in a single policy, but their failures are hard to diagnose once vis

Echoes of Human Malice in Agents: Benchmarking LLMs for Multi-Turn Online Harassment Attacks

arXiv:2510.14207v3 Announce Type: replace Abstract: Large Language Model (LLM) agents are powering a growing share of interactive web applications, yet remain vulnerable to misuse and harm. Prior jail

Efficient Visual Pointing for Embodied AI:Agent-Driven Data Synthesis, Cross-Block Attention, and Iterative Correction

arXiv:2606.29850v1 Announce Type: new Abstract: Visual pointing maps a language instruction to pixel co ordinates, a core skill for embodied AI. We describe our PointArena 2026 solution, which achieve

Emergence of Minimal Circuits for Indirect Object Identification in Attention-Only Transformers

arXiv:2510.25013v2 Announce Type: replace-cross Abstract: Mechanistic interpretability aims to reverse-engineer large language models (LLMs) into human-understandable computational circuits. However,

EMPATH: A Multilingual Auditor-Judge Benchmark for Safety Evaluation of Emotional-Support Chatbots

arXiv:2606.30256v1 Announce Type: new Abstract: Safety benchmarks often buy scalability by fixing the prompt, the language, and the turn structure. For emotional-support chatbots, that bargain hides p

Ensemble Learning Based Classification Algorithm Recommendation

arXiv:2101.05993v2 Announce Type: replace-cross Abstract: Selecting an appropriate classification algorithm for a given data set remains a challenging problem in data mining and machine learning. Exis

Entropy Regularized Reinforcement Learning for Zero-Sum Stochastic Differential Games in a Regime-Switching Jump-Diffusion Process

arXiv:2606.28669v1 Announce Type: new Abstract: To address parameter misspecification and sudden structural environmental changes in conventional stochastic differential game (SDG) frameworks, this pa

Envisage: Diffusion-Based Rhinoplasty Goal Visualization with Mask-Decomposed Evaluation

arXiv:2606.28628v1 Announce Type: cross Abstract: Localized generative editing needs localized evaluation: full-image identity metrics are structurally confounded under hard-composited edits. We prese

EVAF: A Test-Retest Protocol for Selective Parametric Consolidation

arXiv:2606.29916v1 Announce Type: cross Abstract: Long-running language agents need mechanisms for deciding which experiences should persist after the working context is gone. Retrieval systems can re

Eval-Actions: Fine-Grained Execution Quality Evaluation for Robotic Manipulation

model-releasesarxiv-cs-ro

arXiv:2601.18723v2 Announce Type: replace Abstract: Although Vision--Action (VA) and Vision--Language--Action (VLA) policies have advanced robotic manipulation, their evaluation remains dominated by b

EvalSafetyGap: A Hybrid Survey and Conceptual Framework for LLM Evaluation-Safety Failures

arXiv:2606.30219v1 Announce Type: new Abstract: LLM evaluation and AI safety face a shared measurement problem: benchmark scores, reward-model signals, and reported safety metrics can improve while th

Evaluating Memory in LLM Agents via Incremental Multi-Turn Interactions

arXiv:2507.05257v4 Announce Type: replace-cross Abstract: Recent benchmarks for Large Language Model (LLM) agents primarily focus on evaluating reasoning, planning, and execution capabilities, while a

EventVLA: Event-Driven Visual Evidence Memory for Long-Horizon Vision-Language-Action Policies

arXiv:2606.20092v2 Announce Type: replace Abstract: Memory remains a critical bottleneck for long-horizon robotic manipulation, as standard Vision-Language-Action (VLA) policies often fail when task-r

Every article saying 'THIS IS THE NEW JOB OF THE AI ERA' is one of two jobs. And the first is a lie imo. The first job, is usually something…

model-releasesallie-k--miller--x

Every article saying 'THIS IS THE NEW JOB OF THE AI ERA' is one of two jobs. And the first is a lie imo. The first job, is usually something that an AI lab is hiring for and the news blows it complete

EVLA: An Electro-Aware Multimodal Assistant for Physically-Grounded Driving Reasoning and Control

model-releasesarxiv-cs-cl

arXiv:2606.28938v1 Announce Type: new Abstract: Modern vision-language models (VLMs) for driving assistants typically treat vehicle dynamics as a black box, resulting in decisions that lack awareness

Evolutional Math: Cross-Validated Island-Model Genetic Programming for Interpretable Symbolic Regression on Small, Wide Datasets

arXiv:2606.28381v1 Announce Type: cross Abstract: Symbolic regression via genetic programming routinely fails on small, wide datasets - a regime common in clinical-trial monitoring, biostatistics, and

Experience Augmented Policy Optimization for LLM Reasoning

arXiv:2606.30420v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) is a powerful paradigm for improving the reasoning capabilities of large language models (LLMs). H

Expert Evaluation of Clinical AI Tools on Real Point-of-Care Clinical Queries

arXiv:2606.28960v1 Announce Type: new Abstract: Physicians now pose millions of clinical questions to AI tools each week, yet these tools are evaluated largely on hypothetical or exam-style questions,

Explainability-Aware Frustum Attack: Exposing Structural Vulnerabilities in LiDAR-Based 3D Object Detectors

arXiv:2606.29963v1 Announce Type: new Abstract: The structural vulnerabilities of point cloud-based 3D object detectors remain poorly understood. Prior work has studied adversarial robustness primaril

Explaining Attention with Program Synthesis

arXiv:2606.19317v2 Announce Type: replace-cross Abstract: A longstanding goal of research on interpretable deep learning is to replace opaque neural computations with human-meaningful symbolic descrip

Exploiting Local Flatness for Efficient Out-of-Distribution Detection

arXiv:2606.29952v1 Announce Type: cross Abstract: Detecting out-of-distribution (OOD) data is crucial for reliable machine learning deployment. Among detection strategies, post-hoc methods are particu

Explore ideas, scale visual concepts, and start creating: http://goo.gle/4bcThNt

model-releasesgoogle-ai--x

This Google AI post likely promotes a tool or platform for exploring creative ideas, scaling visual concepts, and beginning creative projects, with a shortened URL linking to more details. The post ap

Exploring the Effects of Entanglement on Quantum Machine Learning of Pathogen Epitope-Receptor Binding

arXiv:2606.28655v1 Announce Type: cross Abstract: Parameterized quantum circuits (PQCs) provide a flexible substrate for hybrid quantum machine learning (QML), but their practical value on Noisy Inter

Factorizable Normalizing Flows for parameter-dependent density morphing

arXiv:2606.30489v1 Announce Type: cross Abstract: Normalizing Flows excel at modeling a single fixed density, yet many problems across the sciences, such as high energy physics, instead require modeli

FastPano3D: Feed-Forward Indoor Panoramic 3D Reconstruction from a Single Image

arXiv:2606.30352v1 Announce Type: new Abstract: Recent advances in 3D scene reconstruction have highlighted the intricate trade-offs among rendering quality, inference efficiency, and data dependency.

fev-bench: A Realistic Benchmark for Time Series Forecasting

arXiv:2509.26468v3 Announce Type: replace Abstract: Benchmark quality is critical for meaningful evaluation and sustained progress in time series forecasting, particularly with the rise of pretrained

Few-Shot Domain Incremental Learning via Continual Vision-Language Consolidation

arXiv:2606.30190v1 Announce Type: cross Abstract: Existing domain-incremental learning (DIL) strategies call for massive amounts of data to adapt to new domains and suffer from the overfitting problem

Field Order Should Not Matter: Permutation-Invariant Embedding Model Fine-Tuning for Structured Metadata Retrieval

arXiv:2606.30473v1 Announce Type: cross Abstract: We study retrieval over catalogs of structured metadata, where each record is a small schema whose fields answer different kinds of query. Embedding a

Fine-Tuning General-Purpose Large Language Models for Agricultural Applications:A Reproducible Framework and Evaluation Protocol Based on Qwen3-8B

arXiv:2606.28992v1 Announce Type: cross Abstract: General-purpose large language models (LLMs) have demonstrated strong abilities in opendomain question answering, information extraction, and text gen

FiRe: Frequency Reparameterization as a Preconditioner for Periodic Implicit Neural Representations

arXiv:2606.29414v1 Announce Type: new Abstract: Periodic Implicit Neural Representations (INRs) such as SIREN and FINER assign every neuron, the same global frequency, spending the representational bu

FlatLands: Generative Floormap Completion From a Single Egocentric View

arXiv:2603.16016v2 Announce Type: replace-cross Abstract: A single egocentric image typically captures only a small portion of the floor, yet a complete metric traversability map of the surroundings w

FlipGuard: Defending Large Language Models Against Quantization-Conditioned Backdoor Attacks

arXiv:2606.28962v1 Announce Type: cross Abstract: Model quantization is essential for the efficient deployment of Large Language Models (LLMs), but introduces a critical vulnerability: Quantization-Co

Flow Matching in Feature Space for Stochastic World Modeling

arXiv:2606.29059v1 Announce Type: cross Abstract: World modeling requires forecasting uncertain futures while preserving information useful for downstream perception. Existing visual world models ofte

Forensic Trajectory Signatures for Agent Memory Poisoning Detection

arXiv:2606.30566v1 Announce Type: cross Abstract: We discover a behavioral invariant in LLM agents under persistent memory poisoning: in architectures where routing information is retrieved through ob

Freeze, Prompt, and Adapt: A Framework for Source-free Unsupervised GNN Prompting

arXiv:2505.16903v2 Announce Type: replace Abstract: Prompt tuning has become a key mechanism for adapting pre-trained Graph Neural Networks (GNNs) to new downstream tasks. However, existing approaches

From Accuracy to Visual Dependence: Auditing and Filtering Modality Collapse in Traffic VideoQA

arXiv:2606.30220v1 Announce Type: new Abstract: High benchmark accuracy does not guarantee genuine use of visual evidence. We study this problem in traffic accident Video Question Answering (VideoQA),

From Detecting Agency to Doing Work: Self-Caused Credit Builds a Durable Behavioral Self in a Minimal Spiking Agent

arXiv:2606.30191v1 Announce Type: new Abstract: How does an agent that can tell self from world come to be durably shaped by that distinction? Recent work shows that a predictive system can detect its

From Failure Taxonomy to Intervention: A Diagnostic Methodology for Industry-Scale AVLM in Video and Live-Streaming Platform Moderation

arXiv:2606.30059v1 Announce Type: new Abstract: Industry-scale video and live-streaming moderation imposes requirements that are difficult to satisfy with generic pretrained public models or external

From Fog Chamber to Aircraft Window: Pixel-Registered Imaging and Synthetic Fine-Tuning Enable Cross-Domain Defogging

arXiv:2606.29093v1 Announce Type: new Abstract: A deep defogging pipeline pretrained on controlled laboratory fog and fine-tuned with domain-randomized synthetic fog applied to clear outdoor scenes ge

From Regulatory Approvals to Patents: Cross-Domain Linking for Cardiovascular Device Traceability

arXiv:2606.28353v1 Announce Type: cross Abstract: Linking FDA-approved medical devices to their underlying United States Patent and Trademark Office (USPTO) patents enables critical applications such

From Tool Connection to Execution Control: Benchmarking Security Invariants in MCP-Style Agent Runtimes

arXiv:2606.29073v1 Announce Type: cross Abstract: Model Context Protocol (MCP)-style ecosystems give language-model applications a practical connection layer for tools, resources, prompts, and transpo

Fully solving document parsing includes covering every point on the Pareto curve of accuracy, cost, and latency: 1️⃣ High-accuracy parsing -…

model-releasesjerry-liu--x

Fully solving document parsing includes covering every point on the Pareto curve of accuracy, cost, and latency: 1️⃣ High-accuracy parsing - requires 99%+ accuracy, price insensitive. Especially relev