Search: “model-releases”

Parameter-Free Encoders Remain Viable for RDB Foundation Models

arXiv:2607.05476v1 Announce Type: new Abstract: Given a relational database (RDB) storing heterogeneous tabular information, how can we predict missing (or future) values in some target column of inte

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Model Releases

Partial Symmetry Detection for 3D Geometry using Contrastive Learning with Geodesic Point Cloud Patches

DGX agent

arXiv:2312.08230v2 Announce Type: replace Abstract: Detecting partial extrinsic symmetry in 3D geometry is a fundamental yet persistent challenge in computer vision and graphics, critical for tasks ra

model-releasesarxiv-cs-cv

8 Jul 2026

PatchOptic for Shared-State LLM Workflows with Projected Views and Verified Structured Updates

arXiv:2607.05483v1 Announce Type: cross Abstract: Agentic workflows often operate over shared, structured state. Because LLM context windows are limited, each model invocation is typically shown only

PCBWorld: A Benchmark Environment for Engine-Grounded PCB Design Automation

arXiv:2607.05915v1 Announce Type: new Abstract: PCB routing is the task of connecting the nets of a board with copper traces under strict design rules, yet learning-based methods still lag behind rule

PIPBench: A Profile-Inclusive Framework for Personalized Image Generation Evaluation

arXiv:2607.06440v1 Announce Type: new Abstract: Recent text-to-image models such as DALLE-3 excel at following diverse prompts yet remain blind to individual aesthetic preferences. We study personaliz

Pluralis v0.1: Towards a Multicultural, Multimodal, Multilingual Benchmark for AI Risk and Reliability

model-releasesarxiv-cs-cl

arXiv:2607.06196v1 Announce Type: new Abstract: Current AI safety evaluation and benchmarking frameworks predominantly rely on Western-centric culture-agnostic defaults that mask critical regional law

PluraMath: Extending Mathematical Reasoning Evaluation Beyond High-Resource Languages

arXiv:2607.05992v1 Announce Type: cross Abstract: Mathematical reasoning has become a central task for evaluating and tuning reasoning Large Language Models (LLMs), yet existing benchmarks remain heav

PolicyShiftGuard: Benchmarking and Improving Policy-Adaptive Image Guardrails

arXiv:2607.05910v1 Announce Type: cross Abstract: Image guardrails are typically trained and evaluated under a fixed safety policy, implicitly treating safety as an intrinsic property of an image. Rea

PolyWorkBench: Benchmarking Multilingual Long-Horizon LLM Agents

arXiv:2607.06008v1 Announce Type: new Abstract: Large language model (LLM) agents have shown strong performance in long-horizon tasks that require planning, tool use, and interaction with external env

Population-Level Profiling of DSM-5 Depressive Symptoms Among Self-Reported ADHD and ASD Users on Twitter: An Exploratory Study Using Advanced NLP and Statistical Analysis

model-releasesarxiv-cs-cl

arXiv:2607.05626v1 Announce Type: new Abstract: Background: Depression frequently co-occurs with ADHD and autism spectrum disorder (ASD), but population-level differences in symptom expression between

Privilege and confidentiality in generative AI workflows

arXiv:2607.05479v1 Announce Type: cross Abstract: Generative AI (GenAI) systems store and process client data in three distinct ways: in the model's parameters through training and memorisation, in th

Prompt-Adapter Context Routing for Parameter-Efficient Multi-Shot Long Video Extrapolation

arXiv:2607.06481v1 Announce Type: cross Abstract: We present PACR-Video, a parameter-efficient framework for multi-shot long video extrapolation that preserves recurring entities, scene structure, vis

Quantifying Frontier LLM Capabilities for Container Sandbox Escape

arXiv:2603.02277v2 Announce Type: replace-cross Abstract: Large language models (LLMs) increasingly act as autonomous agents, using tools to execute code, read and write files, and access networks, cr

RFHNet: Relational and Frequency-Aware Hashing Network for Large-Scale Fine-Grained Food Image Retrieval

arXiv:2607.06148v1 Announce Type: new Abstract: Fine-grained food image retrieval is a key task in computational gastronomy, with applications in food traceability, dietary monitoring, and smart cater

RPAM: A Principled Metric for Evaluating Associations in Language Models with High Predictive Validity in Downstream Outputs

arXiv:2607.05679v1 Announce Type: cross Abstract: Language models (LMs) exhibit problematic biases, such as stereotypes. Effectively analyzing and mitigating such biases requires accurate and generali

RuBench: A Repository-Level Agentic Coding Benchmark with Natively Authored Russian Task Specifications

arXiv:2607.06411v1 Announce Type: cross Abstract: Developers increasingly delegate real maintenance work to product-grade coding agents, and many state tasks in their native language, in the style of

SafeImpute: Reliable Clinical Data Imputation via Conformal Selection

arXiv:2607.05613v1 Announce Type: new Abstract: Clinical care often relies on key laboratory indicators, yet real-world patient visits are sparse and tests are ordered irregularly, leading to pervasiv

SAGE: Spatial-visual Adaptive Graph Exploration for Efficient Visual Place Recognition

arXiv:2509.25723v4 Announce Type: replace Abstract: Visual Place Recognition (VPR) requires robust retrieval of geotagged images despite large appearance, viewpoint, and environmental variation. Prior

Scientific Code Search at Scale: A Multi-Domain Dataset and Benchmark

arXiv:2607.05443v1 Announce Type: cross Abstract: Scientists increasingly rely on open-source tools to support their research workflows, yet discovering relevant software among over 600 million GitHub

Self-Review Reinforcement Learning (SRRL) with Cross-Episode Memory and Policy Distillation

arXiv:2607.05541v1 Announce Type: cross Abstract: Reinforcement Learning is commonly used to train large language models using environmental feedback. In applied settings, the environment usually prov

Self-Routing: Parameter-Free Expert Routing from Hidden States

arXiv:2604.00421v2 Announce Type: replace Abstract: Mixture-of-Experts (MoE) layers increase model capacity by activating only a small subset of experts per token, and typically rely on a learned rout

SEVRA-BENCH: Social Engineering of Vulnerabilities in Review Agents

arXiv:2606.13757v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly deployed in automated code-review systems, where their approvals can determine which code is mer

Social 3D Scene Graphs: Modeling Human Actions and Relations for Interactive Service Robots

arXiv:2509.24966v2 Announce Type: replace Abstract: Understanding how people interact with their surroundings and each other is essential for enabling robots to act in socially compliant and context-a

SpanUQ: Span-Level Uncertainty Quantification for Large Language Model Generation

model-releasesarxiv-cs-cl

arXiv:2607.05721v1 Announce Type: new Abstract: Uncertainty estimation is essential not only for the trustworthy deployment of large language models (LLMs) but also as a foundation for self-refinement

Sparse but Wrong: Incorrect L0 Leads to Incorrect Features in Sparse Autoencoders

arXiv:2508.16560v4 Announce Type: replace-cross Abstract: Sparse Autoencoders (SAEs) extract features from LLM internal activations, meant to correspond to interpretable concepts. A core SAE training

Spider 2.0-AIFunc: Extending Real-World Text-to-SQL to AI-Native SQL Workflows

arXiv:2607.06229v1 Announce Type: cross Abstract: Major cloud data platforms now expose large language model capabilities as native SQL functions, enabling analysts to perform classification, filterin

Statistically Meaningful Geometry and Gauge Symmetry Breaking: A Geometric Foundation for Scientific Discovery and Intelligence Emergence

arXiv:2607.05436v1 Announce Type: new Abstract: The rapid scaling of over-parameterized machine learning architectures, particularly LLMs, raises a profound crisis: do these systems exhibit genuine in

StepShield: When, Not Whether to Intervene on Rogue Agents

arXiv:2601.22136v2 Announce Type: replace-cross Abstract: Agent safety benchmarks measure whether a monitor detects harm, not when. Yet timing is the difference between intervention and autopsy. We in

Structured Data Extraction from Real Estate Documents using Clustering, Classification, and Large Language Models

arXiv:2607.06012v1 Announce Type: new Abstract: Real estate property listings expose structured metadata through the API. Still, the richest property-level information (i.e., legal status, structural

Supervised Reward Inference

arXiv:2502.18447v2 Announce Type: replace Abstract: Existing approaches to reward inference typically assume that humans provide demonstrations according to specific behavior models. However, humans o

The Balkanization of Execution-Security Research for AI Coding Agents: Isolation, Access Control, and Time-of-Check-to-Time-of-Use Vulnerabilities

arXiv:2607.05743v1 Announce Type: cross Abstract: AI coding agents now read repositories, call tools, and execute shell commands with limited human oversight, and a fast-growing body of work studies w

The Granularity Paradox: How Temporal Disaggregation Inflates In-Sample Fit and Compounds Out-of-Sample Error

arXiv:2607.05450v1 Announce Type: cross Abstract: This paper explores the 'Granularity Paradox' in time-series forecasting, wherein finer temporal disaggregation (e.g., Monthly to Weekly/Daily) improv

The relationship between reasoning and performance in large language models--o3 (mini) thinks harder, not longer

arXiv:2502.15631v2 Announce Type: replace-cross Abstract: Large language models have demonstrated remarkable progress in mathematical reasoning, leveraging chain-of-thought and reinforcement learning.

The yes-no bias of large language models reflects answer order and wording, not shifts in moral judgment

arXiv:2607.05552v1 Announce Type: cross Abstract: Large language models (LLMs) increasingly issue judgments read as binary verdicts, and a growing literature reports such judgments shifting under logi

Think Before You Grid-Search: Floor-First Triage for LLM Serving

arXiv:2607.05876v1 Announce Type: cross Abstract: LLM serving optimization typically benchmarks many configurations and reaches for heavy profilers when latency targets are missed. We argue for the re

ThorArena: Benchmarking Humanoid Physical Interaction with Human Motion-Force Demonstrations

model-releasesarxiv-cs-ro

arXiv:2607.06052v1 Announce Type: new Abstract: Humanoid robots are increasingly expected to perform contact-rich tasks that require not only accurate whole-body motion but also robust physical intera

Transformers converge to invariant algorithmic cores

arXiv:2602.22600v2 Announce Type: replace-cross Abstract: Training selects for behavior, not circuitry: many weight configurations can implement the same function. Studying any single trained neural n

UI2App: Benchmarking Visual Interaction Inference in Executable Web Application Generation

arXiv:2607.06306v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated growing competence in web page generation. However, existing text-driven approaches rely on complex pro

UniLM-Nav: A Unified Framework for Zero-Shot Last-Mile Navigation

model-releasesarxiv-cs-ro

arXiv:2607.06537v1 Announce Type: new Abstract: Mobile manipulation requires a robot to navigate to a target object or receptacle and then perform intended manipulation. However, reaching the vicinity

VendorBench-100: A Unified Cross-Paradigm Benchmark for Deepfake Image Detection

arXiv:2607.06254v1 Announce Type: cross Abstract: Deepfake image detection is currently served by three fundamentally different paradigms: commercial APIs, zero-shot vision-language models (LLMs), and

Verification of Dynamic Holographic Behavior in Identity Documents

arXiv:2607.06466v1 Announce Type: new Abstract: This paper addresses the remote verification of the authenticity of Optically Variable Devices (commonly known as holograms) on identity documents. Typi

VisCoP: Visual Probing for Video Domain Adaptation of Vision Language Models

arXiv:2510.13808v2 Announce Type: replace Abstract: Large Vision Language Models (VLMs) excel at general visual reasoning but experience significant performance degradation when deployed in novel doma

WebRetriever: A Large-Scale Comprehensive Benchmark for Efficient Web Agent Evaluation

arXiv:2607.06118v1 Announce Type: new Abstract: As web agents increasingly demonstrate capabilities in automated task execution, the development of robust evaluation frameworks for assessing their nav

When Should LLMs Search? Counterfactual Supervision for Search Routing

arXiv:2607.05752v1 Announce Type: cross Abstract: Search-augmented language models can use external evidence to compensate for limitations in parametric knowledge, but search is not uniformly benefici

Why does Deep Learning Improve Visual SLAM?

arXiv:2607.06023v1 Announce Type: new Abstract: Visual SLAM is a well-established technology utilized in a wide range of real-world applications. However, its performance still degrades under challeng

x-Prediction Is All You Need:Training-Free Accelerated Generation via Endpoint Decodability

arXiv:2607.06114v1 Announce Type: cross Abstract: Diffusion and flow matching models generate high-quality samples, but their ODE samplers often need tens to hundreds of neural function evaluations (N

XRFormer: Multiscale Tokenization for XRF Representation Learning

arXiv:2607.06424v1 Announce Type: new Abstract: X-ray fluorescence (XRF) spectroscopy is a key modality for material analysis in cultural heritage. However, automated learning from XRF spectra remains

ZeroBench: An Impossible Visual Benchmark for Contemporary Large Multimodal Models

arXiv:2502.09696v3 Announce Type: replace Abstract: Large Multimodal Models (LMMs) exhibit shortfalls when interpreting images and, by some measures, have poorer spatial cognition than young children