Search: “model-releases”

Optimal FALQON for Quantum Approximate Optimization via Layer-wise Parameter Tuning

arXiv:2605.08332v1 Announce Type: cross Abstract: Feedback-based adaptive quantum optimization (FALQON) is a promising approach for solving combinatorial problems on noisy intermediate-scale quantum (

Model Releases

Optimality of Sub-network Laplace Approximations: New Results and Methods

DGX agent

arXiv:2605.09075v1 Announce Type: cross Abstract: Although the Laplace approximation offers a simple route to uncertainty quantification in deep neural networks, its reliance on inverting large Hessia

model-releasesarxiv-cs-lg

12 May 2026

Optimised Support Vector Regression for California Housing Price Prediction: The Critical Role of Feature Engineering and Hyperparameter Tuning

arXiv:2605.08660v1 Announce Type: new Abstract: In the recent literature, Support Vector Regression (SVR) has been cited as one of the weakest performers on the California Housing benchmark dataset, w

Optimized Culprit Identification Using Mobilenet and Attention Mechanisms

arXiv:2605.08169v1 Announce Type: cross Abstract: Automated culprit identification in surveillance systems is a critical task that requires high accuracy along with computational efficiency for real-t

Oracle Poisoning: Corrupting Knowledge Graphs to Weaponise AI Agent Reasoning

arXiv:2605.09822v1 Announce Type: cross Abstract: We define Oracle Poisoning, an attack class in which an adversary corrupts a structured knowledge graph that AI agents query at runtime via tool-use p

OracleTSC: Oracle-Informed Reward Hurdle and Uncertainty Regularization for Traffic Signal Control

arXiv:2605.08516v1 Announce Type: new Abstract: Transparent decision-making is essential for traffic signal control (TSC) systems to earn public trust. However, traditional reinforcement learning-base

OrderFusion: Encoding Orderbook for End-to-End Probabilistic Intraday Electricity Price Forecasting

arXiv:2502.06830v5 Announce Type: replace-cross Abstract: Probabilistic intraday electricity price forecasting is becoming increasingly important for short-term power-system operation. With increasing

OTora: A Unified Red Teaming Framework for Reasoning-Level Denial-of-Service in LLM Agents

arXiv:2605.08876v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed as autonomous agents that execute tool-augmented, multi-step tasks, where latency is a critical f

Overconfident and Blind to Details: Fixing Prompt Insensitivity with Abductive Preference Learning

model-releasesarxiv-cs-cl

arXiv:2510.09887v2 Announce Type: replace Abstract: Vision and language models frequently ignore semantically critical input edits, defaulting to pretraining priors. For example, models will confident

Pairwise is Not Enough: Hypergraph Neural Networks for Multi-Agent Pathfinding

arXiv:2602.06733v2 Announce Type: replace-cross Abstract: Multi-Agent Path Finding (MAPF) is a representative multi-agent coordination problem, where multiple agents are required to navigate to their

PaperFit: Vision-in-the-Loop Typesetting Optimization for Scientific Documents

arXiv:2605.10341v1 Announce Type: new Abstract: A LaTeX manuscript that compiles without error is not necessarily publication-ready. The resulting PDFs frequently suffer from misplaced floats, overflo

Parallel Multi-Circuit Quantum Feature Fusion in Hybrid Quantum-Classical Convolutional Neural Networks for Breast Tumor Classification

arXiv:2512.02066v2 Announce Type: replace-cross Abstract: Quantum machine learning has emerged as a promising approach to improve feature extraction and classification tasks in high-dimensional data d

Parameter-Efficient Neuroevolution for Diverse LLM Generation: Quality-Diversity Optimization via Prompt Embedding Evolution

arXiv:2605.09781v1 Announce Type: cross Abstract: Large Language Models exhibit mode collapse, producing homogeneous outputs that fail to explore valid solution spaces. We present QD-LLM, a framework

parameter golf was a blast. 2,000+ submissions. 1,000+ verified github accounts. ideas ranging from quantization and depth recurrence to TTT…

parameter golf was a blast. 2,000+ submissions. 1,000+ verified github accounts. ideas ranging from quantization and depth recurrence to TTT LoRA, SSMs, H-nets, JEPA, and more. autoresearch made itera

model-releasesopenai--x

Parameterized Complexity of Stationarity Testing for Piecewise-Affine Functions and Shallow CNN Losses

arXiv:2605.10219v1 Announce Type: cross Abstract: We study the parameterized complexity of testing approximate first-order stationarity at a prescribed point for continuous piecewise-affine (PA) funct

Path-Based Gradient Boosting for Graph-Level Prediction

arXiv:2605.08102v1 Announce Type: new Abstract: We propose PathBoost, a gradient tree boosting method for graph-level classification and regression that learns discriminative path-based features direc

PDEAgent-Bench: A Multi-Metric, Multi-Library Benchmark for PDE Solver Generation

arXiv:2605.09636v1 Announce Type: new Abstract: PDE-to-solver code generation aims to automatically synthesize executable numerical solvers from partial differential equation (PDE) specifications. Thi

Per-Loss Adapters for Gradient Conflict in Physics-Informed Neural Networks

arXiv:2605.10136v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) train a single neural approximation by minimizing multiple physics- and data-derived losses, but the gradients

Personal Visual Context Learning in Large Multimodal Models

arXiv:2605.10936v1 Announce Type: new Abstract: As wearable devices like smart glasses integrate Large Multimodal Models (LMMs) into the continuous first-person visual streams of individual users, the

Personalized Alignment Revisited: The Necessity and Sufficiency of User Diversity

arXiv:2605.09119v1 Announce Type: cross Abstract: Personalized alignment aims to adapt large language models to heterogeneous user preferences, yet the precise theoretical conditions for its statistic

PHIDA: Persistence-Guided Node-to-Cluster Mapping for Online Clustering

arXiv:2605.08673v1 Announce Type: new Abstract: Online clustering methods that adaptively create and update nodes as data arrive often make node learning explicit, whereas the mapping from the learned

Phoenix-VL 1.5 Medium Technical Report

arXiv:2605.10391v1 Announce Type: cross Abstract: We introduce Phoenix-VL 1.5 Medium, a 123B-parameter natively multimodal and multilingual foundation model, adapted to regional languages and the Sing

PhyGround: Benchmarking Physical Reasoning in Generative World Models

arXiv:2605.10806v1 Announce Type: cross Abstract: Generative world models are increasingly used for video generation, where learned simulators are expected to capture the physical rules that govern re

PINS: Proximal Iterations with Sparse Newton and Sinkhorn for Optimal Transport

arXiv:2502.03749v2 Announce Type: replace Abstract: Optimal transport (OT) is a widely used tool in machine learning, but computing high-accuracy solutions for large instances remains costly. Entropic

Pix2Fact: When Vision Is Not Enough -- Benchmarking Fine-Grained VQA with Web Verification on High-Resolution Real-World Scenes

arXiv:2602.00593v2 Announce Type: replace Abstract: Despite progress on general tasks, vision-language models (VLMs) still struggle with challenges that demand both fine-grained visual grounding and e

PlantMarkerBench: A Multi-Species Benchmark for Evidence-Grounded Plant Marker Reasoning

model-releasesarxiv-cs-cl

arXiv:2605.10032v1 Announce Type: new Abstract: Cell-type-specific marker genes are fundamental to plant biology, yet existing resources primarily rely on curated databases or high-throughput studies

PolarVSR: A Unified Framework and Benchmark for Continuous Space-Time Polarization Video Reconstruction

arXiv:2605.10275v1 Announce Type: new Abstract: Polarimetric imaging captures surface polarization characteristics, such as the Degree of Linear Polarization (DoLP) and the Angle of Polarization (AoP)

Polymath: A Challenging Multi-modal Mathematical Reasoning Benchmark

arXiv:2410.14702v2 Announce Type: replace Abstract: Multi-modal Large Language Models (MLLMs) exhibit impressive problem-solving abilities in various domains, but their visual comprehension and abstra

Position: AI Security Policy Should Target Systems, Not Models

arXiv:2605.09504v1 Announce Type: cross Abstract: We present swarm-attack, an open-source adversarial testing framework in which multiple lightweight LLM agents coordinate through shared memory, paral

Position: Stop Evaluating AI with Human Tests, Develop Principled, AI-specific Tests instead

arXiv:2507.23009v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have achieved remarkable results on a range of standardized tests originally designed to assess human cognitive a

PPU-Bench:Real World Benchmark for Personalized Partial Unlearning in Vision Language Models

arXiv:2605.08800v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) may memorize sensitive cross-modal information during pretraining. However, existing MLLM unlearning benchmar

PrAg-PO: Prompt Augmented Policy Optimization for Robust and Diverse Mathematical Reasoning

arXiv:2602.03190v3 Announce Type: replace-cross Abstract: Reinforcement learning algorithms such as group-relative policy optimization (GRPO) have shown strong potential for improving the mathematical

Prediction Bottlenecks Don't Discover Causal Structure (But Here's What They Actually Do)

arXiv:2605.09169v1 Announce Type: cross Abstract: A Mamba state-space model trained only for next-step prediction appears to recover Granger-causal structure through a simple readout S = |W_{out} W_{i

PrepBench: How Far Are We from Natural-Language-Driven Data Preparation?

arXiv:2605.08687v1 Announce Type: cross Abstract: Data preparation is a central and time-consuming stage in data analysis workflows. Traditionally, commercial tools have relied on graphical user inter

Preserve and Personalize: Personalized Text-to-Image Diffusion Models without Distributional Drift

arXiv:2505.19519v3 Announce Type: replace Abstract: Personalizing text-to-image diffusion models involves integrating novel visual concepts from a small set of reference images while retaining the mod

Preserving Foundational Capabilities in Flow-Matching VLAs through Conservative SFT

model-releasesarxiv-cs-ro

arXiv:2605.08879v1 Announce Type: new Abstract: Unconstrained fine-tuning of flow-matching Vision-Language-Action (VLA) models drives dense parameter overwrites, degrading pre-trained capabilities. We

Pretraining large language models with MXFP4

arXiv:2605.09825v1 Announce Type: cross Abstract: Why does full-pipeline FP4 training of large language models often diverge, even when forward activations and activation gradients remain stable? We a

PRIM: Meta-Learned Bayesian Root Cause Analysis

arXiv:2605.08786v1 Announce Type: new Abstract: Root cause analysis (RCA) in complex systems is challenging due to error propagation across multiple variables, the need for structural causal knowledge

PrimeKG-CL: A Continual Graph Learning Benchmark on Evolving Biomedical Knowledge Graphs

arXiv:2605.10529v1 Announce Type: new Abstract: Biomedical knowledge graphs underwrite drug repurposing and clinical decision support, yet the upstream ontologies they depend on update on independent

Priming: Hybrid State Space Models From Pre-trained Transformers

arXiv:2605.08301v1 Announce Type: cross Abstract: Hybrid State-Space models combine Attention with recurrent State-Space Model (SSM) layers, balancing eidetic memory from Attention with compressed fad

Priority-Driven Control and Communication in Decentralized Multi-Agent Systems via Reinforcement Learning

arXiv:2605.10482v1 Announce Type: cross Abstract: Event-triggered control provides a mechanism for avoiding excessive use of constrained communication bandwidth in networked multi-agent systems. Howev

PRISM: Generation-Time Detection and Mitigation of Secret Leakage in Multi-Agent LLM Pipelines

arXiv:2605.10614v1 Announce Type: new Abstract: Multi-agent LLM systems introduce a security risk in which sensitive information accessed by one agent can propagate through shared context and reappear

Privacy Auditing Synthetic Data Release through Local Likelihood Attacks

arXiv:2508.21146v2 Announce Type: replace Abstract: Auditing the privacy leakage of synthetic data is an important but unresolved problem. Existing privacy auditing frameworks for synthetic data rely

ProactBench: Beyond What The User Asked For

arXiv:2605.09228v1 Announce Type: cross Abstract: Most LLM benchmarks score how well a model responds to explicit requests. They leave unmeasured a different conversational ability: noticing and actin

Probing the Critical Point (CritPt) of AI Reasoning: a Frontier Physics Research Benchmark

arXiv:2509.26574v4 Announce Type: replace Abstract: While large language models (LLMs) with reasoning capabilities are progressing rapidly on high-school math competitions and coding, can they reason

Probing the Impact of Scale on Data-Efficient, Generalist Transformer World Models for Atari

arXiv:2605.08578v1 Announce Type: cross Abstract: Developing generalist systems that retain human-like data efficiency is a central challenge. While world models (WMs) offer a promising path, existing

Process Matters more than Output for Distinguishing Humans from Machines

arXiv:2605.06524v2 Announce Type: replace Abstract: Reliable human-machine discrimination is becoming increasingly important as large language models and autonomous agents are deployed in online setti

Product-of-Gaussian-Mixture Diffusion Models for Joint Nonlinear MRI Reconstruction

arXiv:2605.10629v1 Announce Type: new Abstract: Recently, diffusion models have attracted considerable attention for magnetic resonance image reconstruction due to their high sample quality. However,