Search: “models”

Generating Input Distributions for Explaining Portfolio Optimization Pipelines

arXiv:2606.25808v1 Announce Type: cross Abstract: We propose a predict-optimize-explain framework that uses gradient-based sample generation to interpret various portfolio models by identifying macroe

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Latent Block-Diffusion Temporal Point Processes: A Semi-Autoregressive Framework for Asynchronous Event Sequence Generation

DGX agent

arXiv:2606.24982v1 Announce Type: new Abstract: Modeling and sampling from the underlying distribution of asynchronous event sequences are crucial in various real-world applications, including social

model-releasesarxiv-cs-lg

25 Jun 2026

Safety

Learning Action Priors for Cross-embodiment Robot Manipulation

arXiv:2606.26095v1 Announce Type: cross Abstract: Most Vision-Language-Action (VLA) models build on a Vision-Language Model (VLM) backbone by attaching an action module and optimizing the full policy

safetyarxiv-cs-cv

Memory-Efficient Policy Libraries with Low-Rank Adaptation in Reinforcement Learning

arXiv:2606.25700v1 Announce Type: new Abstract: When fine-tuning Large Language Models (LLMs), there has been success in minimizing both memory usage and computation with Parameter-Efficient Fine-Tuni

PatchINR: Patch-Based Implicit Neural Representations for Efficient and Scalable Inference

arXiv:2606.25534v1 Announce Type: new Abstract: Implicit Neural Representation (INR) provides an effective approach for continuous signal modeling, but classical per-pixel inference results in quadrat

Research

PERTINENCE: Input-based Opportunistic Neural Network Dynamic Execution

arXiv:2507.01695v3 Announce Type: replace Abstract: Deep neural networks (DNNs) are widely used for their ability to model complex patterns across domains such as computer vision, speech recognition,

researcharxiv-cs-lg

Project Auto-World: Towards Automated Benchmarking of Neural Relational Reasoners

arXiv:2606.24965v1 Announce Type: cross Abstract: Reasoning about relational structures remains a significant challenge for neural models, particularly when they must systematically apply learned know

RWGBench: Evaluating Scholarly Positioning in Related Work Generation

arXiv:2606.24894v1 Announce Type: cross Abstract: Large language models have shown strong fluency in scientific writing, yet the evaluation of related work generation (RWG) remains limited. Existing R

Silent Failures in Physics-Informed Neural Networks: Parameter Poisoning and the Limits of Loss-Based Validation

arXiv:2606.25151v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) embed governing equations in their loss function, enabling mesh-free solutions to partial differential equation

The 4/elta Bound: Designing Predictable LLM-Verifier Systems for Formal Method Guarantee

arXiv:2512.02080v3 Announce Type: replace-cross Abstract: The integration of Formal Verification tools with Large Language Models (LLMs) offers a path to scale software verification beyond manual work

TopoCast: A Topological Fidelity Framework for Evaluating Transformer-Based Time Series Forecasting

arXiv:2606.25439v1 Announce Type: new Abstract: Deep learning-based models have achieved state-of-the-art performance in Time Series Forecasting (TSF), yet their evaluation remains dominated by pointw

TriViewBench: Controlled Complexity Scaling for Multi-View Structural Reasoning in MLLMs

arXiv:2606.26029v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) demonstrate strong performance on standard visual question answering benchmarks, yet their scalability under co

Type Checking Project Haystack Grids using JSON Schema and Pydantic

arXiv:2606.24891v1 Announce Type: cross Abstract: Ontologies enable scalable energy services in buildings by supporting interoperability and automation. Project Haystack is a building ontology that is

When Multi-Sensor Fusion Fails to Generalize: Cattle Posture Classification Under Animal-Level and Temporal Distribution Shift

arXiv:2606.24986v1 Announce Type: new Abstract: Automated cattle posture-classification systems frequently report near-perfect accuracy, yet their robustness under realistic deployment conditions rema

3DCarGen: Scalable 3D Car Generation via 3D-consistent Multi-view Synthesis

arXiv:2606.24257v1 Announce Type: new Abstract: High-quality 3D vehicle assets are essential for autonomous driving simulation. Although multi-view diffusion-based paradigms enable controllable single

AgentRivet: an automated system for producing Rivet routines from journal publications

arXiv:2606.13535v3 Announce Type: replace-cross Abstract: Particle physics collider experiments provide Rivet routines as part of the analysis preservation strategy for model-independent measurements.

agentsarxiv-cs-ai

Beyond Bayer: Task-Optimal Sensor Co-Design for Robust Autonomous-Driving Segmentation

arXiv:2606.24096v1 Announce Type: cross Abstract: Robust perception underpins autonomous driving, and most recent progress comes from scaling the model-larger backbones, foundation models, and coopera

agentsarxiv-cs-ai

Safety

Beyond Trajectory Imitation: Strategy-Guided Policy Optimization for LLM Reasoning

arXiv:2606.24064v1 Announce Type: new Abstract: Distilling reasoning capabilities from strong to weak language models typically involves imitating specific solution trajectories, effectively transferr

safetyarxiv-cs-ai

Decentralised AI Training and Inference with BlockTrain

arXiv:2606.24722v1 Announce Type: new Abstract: Frontier AI training is increasingly shaped by access to dense, centrally controlled accelerator clusters. This creates a structural advantage for hyper

How Much Can We Trust LLM Search Agents? Measuring Endorsement Vulnerability to Web Content Manipulation

model-releasesarxiv-cs-cl

arXiv:2606.16821v2 Announce Type: replace Abstract: Large language model (LLM)-based search agents synthesize open-web content into actionable recommendations on behalf of users, creating a risk that

Jolia: Concept-Level Vision-Language Alignment for 3D CT Contrastive Learning

arXiv:2606.24570v1 Announce Type: new Abstract: Vision-language contrastive pretraining has become the dominant recipe for 3D medical foundation models, leveraging the large volumes of paired scans an

Knowledge-Graph Grounding Helps LLMs Only for Out-of-Training Knowledge: A Controlled Study on Clinical Question Answering

model-releasesarxiv-cs-cl

arXiv:2606.22419v2 Announce Type: replace Abstract: A recent Nature Medicine study reports that general-purpose frontier LLMs outperform specialized retrieval-augmented clinical tools on medical bench

Mind the Heads: Topological Representation Alignment for Multimodal LLMs

arXiv:2606.23885v1 Announce Type: cross Abstract: Representation alignment has emerged as an effective approach to improve Multimodal Large Language Models (MLLMs) by regularizing their internal repre

Modality-Aware Out-of-Distribution Detection for Multi-Modal Action Recognition

arXiv:2606.24404v1 Announce Type: new Abstract: The incorporation of additional modalities into action recognition models increases their performance across a wide range of settings. However, how this

Point-Voxel Absorbing Graph Representation Learning for Event Stream based Recognition

arXiv:2306.05239v3 Announce Type: replace Abstract: Sampled point and voxel methods are usually employed to downsample the dense events into sparse ones. After that, one popular way is to leverage a g

Research

Posterior Refinement: Fast Language Generation via Any-Order Flow Maps

arXiv:2606.24773v1 Announce Type: new Abstract: Non-autoregressive generation offers a powerful paradigm for iterative refinement, allowing models to recursively critique, erase and regenerate arbitra

researcharxiv-cs-cl

Privacy-Preserving RAG via Multi-Agent Semantic Rewriting: Achieving Confidentiality Without Compromising Contextual Fidelity

arXiv:2606.24623v1 Announce Type: cross Abstract: Retrieval-Augmented Generation enhances large language models by incorporating external knowledge, but deploying it in sensitive scenarios risks priva

Project Ariadne: Prompt-Conditioned Route Generation for Synthesis Planning

arXiv:2606.24184v1 Announce Type: new Abstract: Retrosynthetic planning seeks to connect a target molecule to commercially available starting materials through a multistep route. Classical planners co

Rule2Text: A Framework for Generating and Evaluating Natural Language Explanations of Knowledge Graph Rules

arXiv:2508.10971v2 Announce Type: replace-cross Abstract: Knowledge graphs (KGs) can be enhanced through rule mining; however, the resulting logical rules are often difficult for humans to interpret d

SignNet-1M: Large-Scale Multilingual Sign Language Video Dataset with Downstream Benchmarks

arXiv:2606.24361v1 Announce Type: new Abstract: Sign language models are typically trained on datasets captured under constrained conditions, with limited viewpoint, background, and signer-identity di

Sol Video Inference Engine: Agent-Native Full-Stack Acceleration Framework for Efficient Video Generation

arXiv:2606.23743v1 Announce Type: cross Abstract: Modern video diffusion models achieve higher generation quality through scaling, but this also increases inference cost. Although many acceleration me

agentsarxiv-cs-ai

The African Language Tax: Quantifying the Cost, Latency, and Context Penalty of Tokenizing African Languages in Frontier LLMs

arXiv:2606.24460v1 Announce Type: cross Abstract: Commercial large language models bill, scale latency, and budget context per token. Yet tokenizers assign more subword tokens to the same meaning in s

The Degeneracy Distillery

arXiv:2606.23838v1 Announce Type: new Abstract: When two or more parameters or labels produce similar data, they are degenerate, or hard to distinguish. Degeneracies render both label prediction and i

VisCritic: Visual State Comparison as Process Reward for GUI Agents

arXiv:2606.24525v1 Announce Type: new Abstract: GUI agents powered by vision-language models show strong potential for automating digital tasks, yet frequently fail in long-horizon scenarios due to th

AD-Bench: A Real-World, Trajectory-Aware Advertising Analytics Benchmark for LLM Agents

arXiv:2602.14257v2 Announce Type: replace-cross Abstract: While Large Language Model (LLM) agents have made remarkable progress on complex reasoning, evaluating them in real-world environments remains

Tutorials

Adversarial Domain Prompt Tuning and Generation for Single Domain Generalization

arXiv:2606.21736v1 Announce Type: new Abstract: Single domain generalization (SDG) aims to learn a robust model, which could perform well on many unseen domains while there is only one single domain a

tutorialsarxiv-cs-cv

Research

Aligning AI-driven discovery with human intuition

arXiv:2410.07397v2 Announce Type: replace Abstract: As data-driven modeling of physical dynamical systems becomes more prevalent, a new challenge is emerging: making these models more compatible and a

researcharxiv-cs-lg

BIFE: Better Interaction, Fewer Errors for Minute-Long Video Generation

arXiv:2511.22973v2 Announce Type: replace Abstract: Long video generation is a critical step toward building realistic world models, requiring both high visual fidelity and long-range interaction cons

Tutorials

BoxCtrl: 3D-Aware Visual Prompting for Geometric Image Editing

arXiv:2606.23270v1 Announce Type: new Abstract: As instruction-based editing models and multimodal large language models advance, diverse image editing tasks have become feasible. However, achieving p

tutorialsarxiv-cs-cv

CAOA -- Completion-Assisted Object-CAD Alignment

arXiv:2606.18429v2 Announce Type: replace Abstract: Accurately aligning CAD models to their corresponding objects in indoor RGB-D scans is a central challenge in 3D semantic reconstruction. The task r

Catching Lies Without Sending the Video: Privacy-Preserving Multimodal Deception Detection

arXiv:2606.22699v1 Announce Type: new Abstract: Frontier multimodal models can guess whether a person is lying from a testimony video. To do so, they stream that raw face and voice to a third-party mo

Causal Discovery in the Era of Agents

arXiv:2606.23608v1 Announce Type: cross Abstract: Recent attempts to combine large language models (LLMs) with causal discovery ask models to infer pairwise directions, propose graph structures, or in

agentsarxiv-cs-lg

Chains That See, Answers That Don't: A Multi-Aspect Evaluation Recipe for Forced Chain-of-Thought on Video-MME

arXiv:2606.22862v1 Announce Type: new Abstract: Forced chain-of-thought (CoT) is widely assumed to make vision-language models more reliable on video question answering. We propose a small three-probe

CheXpercept: A Benchmark for Evaluating Expert-Level Lesion Perception in Chest X-rays

arXiv:2606.21020v1 Announce Type: new Abstract: The evaluation of vision-language models (VLMs) for chest X-ray (CXR) analysis has largely been limited to disease-presence classification without visua

ChronoLock: Protecting Videos from Unauthorized Text-to-Video Personalization

arXiv:2606.21146v1 Announce Type: new Abstract: Text-to-video (T2V) diffusion models have made it increasingly easy to synthesize realistic and temporally coherent videos, while recent personalization

Clipping the Price of Adaptivity at the Tail

arXiv:2606.22669v1 Announce Type: new Abstract: Adaptive stochastic convex optimization (SCO) methods face a fundamental ``price of adaptivity'' barrier: under the standard set of assumptions, they ca

Disentangling Intrinsic Importance from Emergent Structure in Multi-Expert Orchestration

arXiv:2602.04291v2 Announce Type: replace Abstract: Multi-expert systems, where multiple Large Language Models (LLMs) collaborate to solve complex tasks, are increasingly adopted for high-performance

EBench: Elemental Diagnosis of Generalist Mobile Manipulation Policies

model-releasesarxiv-cs-ro

arXiv:2606.18239v2 Announce Type: replace Abstract: We present EBench, a simulation benchmark that diagnoses generalist mobile manipulation policies beyond a single success-rate scalar. EBench compris