Search: “model-releases”

On the Subgaussianity of Quantized Linear Maps: An AI-Assisted Note

arXiv:2605.27563v1 Announce Type: cross Abstract: This short note presents a dimension-independent subgaussian concentration bound for Gaussian vectors under coordinate-wise nonlinear mappings. Discov

Optimal LTLf Synthesis

DGX agent

arXiv:2605.11544v2 Announce Type: replace Abstract: Strategy synthesis typically follows an all-or-nothing paradigm, returning unrealisable whenever a specification cannot be guaranteed in an uncertai

model-releasesarxiv-cs-ai

28 May 2026

Optimal ridge regularization revisited

arXiv:2605.28679v1 Announce Type: new Abstract: We consider L^2-regularized linear (ridge) regression over a finite data sample X with bounded covariance and linear prediction targets y with additive

Opus 4.8 formulated the hypotheses in advance, conducting data cleaning, did research on references, conducted analyses, did robustness chec…

model-releasesethan-mollick--x

Opus 4.8 formulated the hypotheses in advance, conducting data cleaning, did research on references, conducted analyses, did robustness checks, and put out the whole paper in LaTEX style. GPT-5.5 foun

OR-Space: A Full-Lifecycle Workspace Benchmark for Industrial Optimization Agents

arXiv:2605.28158v1 Announce Type: new Abstract: Large language model (LLM) agents are increasingly used to assist with operations research (OR) modeling, yet existing OR-oriented benchmarks often redu

OralAgent: Integrating Reasoning, Tools, and Knowledge for Interactive Dental Image Analysis

arXiv:2605.27378v1 Announce Type: new Abstract: Dental image analysis plays a pivotal role in supporting accurate diagnosis and treatment planning in oral healthcare. Although recent advances have pro

Parameter-Efficient Generative Modeling with Controlled Vector Fields

arXiv:2605.28267v1 Announce Type: new Abstract: We introduce a continuous-time generative modeling framework, motivated by the Chow-Rashevskii theorem, that builds expressive flows from a small set of

Paraphrase Brittleness in Production Retrieval-Augmented Commercial Recommendation: Reproducibility Below the Rerun-Stability Baseline

arXiv:2605.27440v1 Announce Type: cross Abstract: Small changes to how a buyer phrases a question -- 'best CRM' vs 'top CRM' vs 'best CRM for a SaaS startup' -- produce substantially different brand r

Particle-Guided Diffusion Models for Partial Differential Equations

arXiv:2601.23262v2 Announce Type: replace Abstract: We introduce a guided stochastic sampling method that augments sampling from diffusion models with physics-based guidance derived from partial diffe

PAST2HARM: A Simple Adaptive Past Tense Attack for Jailbreaking Multimodal AI

arXiv:2605.27545v1 Announce Type: new Abstract: Jailbreak attacks on multimodal AI systems remain underexplored, even though unsafe image generation can have more severe consequences than unsafe text

Patched-DeltaNet: Token-Level Event-Driven Memory for Linear-Time Anomaly Detection

arXiv:2605.27992v1 Announce Type: new Abstract: Time series anomaly detection is critical for maintaining the reliability of mission-critical systems. While Transformer-based models like PatchTST have

PEAM: Parametric Embodied Agent Memory through Contrastive Internalization of Experience in Minecraft

arXiv:2605.27762v1 Announce Type: new Abstract: We present PEAM, a Parametric Embodied Agent Memory framework in Minecraft that transforms agent memory from inference-time retrieval into parameter-res

PEAR: Pairwise Evaluation for Automatic Relative Scoring in Machine Translation

arXiv:2601.18006v2 Announce Type: replace Abstract: We present PEAR (Pairwise Evaluation for Automatic Relative Scoring), a supervised quality estimation (QE) metric family that reframes reference-fre

PEFT-Arena: Understanding Parameter-Efficient Finetuning from a Stability-Plasticity Perspective

arXiv:2605.28819v1 Announce Type: cross Abstract: Parameter-efficient finetuning (PEFT) has become the standard approach for adapting large language models, yet evaluations largely emphasize downstrea

Periodic RoPE for Infinite Context LLMs

arXiv:2605.27980v1 Announce Type: cross Abstract: The ability to process ultra-long contexts is crucial for large language models (LLMs) to perform long-horizon tasks. While recent efforts have extend

Personal Visual Memory from Explicit and Implicit Evidence

arXiv:2605.28806v1 Announce Type: cross Abstract: Long-term memory is increasingly important for personalized AI agents, yet existing benchmarks and methods remain largely text-centric. Even when imag

Personalized Observation Normalization for Federated Reinforcement Learning in Simulation Environments with Heterogeneity

arXiv:2605.27385v1 Announce Type: cross Abstract: Federated reinforcement learning (FedRL) enables multiple agents to collaboratively train a global policy without sharing raw data, making it ideal fo

Persuade Me if You Can: A Framework for Evaluating Persuasion Effectiveness and Susceptibility Among Large Language Models

arXiv:2503.01829v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) demonstrate persuasive capabilities that rival human-level persuasion. While these capabilities can be used for s

PetroBench: A Benchmark for Large Language Models in Petroleum Engineering

arXiv:2605.28032v1 Announce Type: new Abstract: Large Language Models are increasingly applied in the petroleum industry, highlighting the need for a domain-specific evaluation framework. This study d

PINE: Pruning Boosted Tree Ensembles with Conformal In-Distribution Prediction Equivalence

arXiv:2605.28068v1 Announce Type: new Abstract: Tree ensembles are machine learning models with strong predictive performance and interpretability, and remain widely used for tabular data. Standard pr

Pittsburgh-based Gray Swan, which stress-tests AI models for top frontier AI labs, raised a 40M Series A at a 200M valuation co-led by Wing VC and Madrona (Rashi Shrivastava/Forbes)

Rashi Shrivastava / Forbes: Pittsburgh-based Gray Swan, which stress-tests AI models for top frontier AI labs, raised a 40M Series A at a 200M valuation co-led by Wing VC and Madrona — Gray Swan works

model-releasestechmeme

Plant, Persist, Trigger: Sleeper Attack on Large Language Model Agents

arXiv:2605.28201v1 Announce Type: new Abstract: Large Language Model (LLM) agents remain vulnerable to safety threats from the external environment, where attackers inject adversarial content into ext

Plug-and-Play Benchmarking of Reinforcement Learning Algorithms for Large-Scale Flow Control

arXiv:2601.15015v2 Announce Type: replace Abstract: Reinforcement learning (RL) has shown promising results in active flow control (AFC), yet progress in the field remains difficult to assess as exist

POINav: Benchmarking and Enhancing Final-Meters Arrival in Real-World Vision-Language Navigation

arXiv:2605.28237v1 Announce Type: cross Abstract: Real-world navigation is fundamentally driven by Points of Interest (POIs), yet reaching a precise POI remains a critical 'final-meters' challenge. Ex

PointQ-Bench: Benchmarking Diagnostic and Interpretable Point Cloud Quality Assessment

arXiv:2605.28241v1 Announce Type: new Abstract: Point cloud quality plays a critical role in 3D acquisition, reconstruction, rendering, and perception, yet existing point cloud quality assessment (PCQ

PortBench: A Correlation-Aware, Full-Pipeline Benchmark for LLM-Driven Portfolio Management

arXiv:2605.27887v1 Announce Type: new Abstract: LLMs have shown strong performance across diverse financial tasks, yet portfolio management (PM), a critical financial decision-making task, remains poo

Pressure-Testing Deception Probes in LLMs: Scaling, Robustness, and the Geometry of Deceptive Representations

arXiv:2605.27958v1 Announce Type: cross Abstract: Linear probes trained on LLM activations are increasingly proposed as deception-detection metrics, yet report AUROC exceeding 0.96 on clean benchmarks

PrionNER: A Named Entity Recognition Dataset for Prion Disease Biomedical Literature

arXiv:2605.28375v1 Announce Type: new Abstract: Prion diseases are rare, rapidly progressive, and fatal neurodegenerative disorders that remain difficult to diagnose, particularly in their early stage

Privately Estimating Monotone Statistics in Polynomial Time

arXiv:2605.27912v1 Announce Type: cross Abstract: We study efficient differentially private algorithms for estimating monotone statistics, i.e., statistics that are monotone under the addition of new

Probabilistic Data-Driven Modelling of Astrophysical Transients: The Neural Process Family for Ultrafast and Class-Agnostic Light Curve Reconstruction with NightLANP

arXiv:2605.27527v1 Announce Type: cross Abstract: Astrophysical observations taken from Earth are subject to weather, environmental, and scientific constraints that lead to sparse, irregular light cur

Probing for Knowledge Attribution in Large Language Models

arXiv:2602.22787v2 Announce Type: replace-cross Abstract: Large language model (LLM) hallucinations, meaning fluent but factually incorrect generations, fall into two types: faithfulness violations, w

ProgVLA: Progress-Aware Robot Manipulation Skill Learning

arXiv:2605.28231v1 Announce Type: cross Abstract: We present ProgVLA, a compact vision-language-action (VLA) model designed for reliable robot manipulation under tight compute and memory budgets. The

Prominence-Stratified Failure Modes in Retrieval-Augmented Commercial Recommendation: A 37,000-Run Audit

arXiv:2605.27439v1 Announce Type: cross Abstract: AI assistants like ChatGPT and Claude are recommendation engines, not search engines: they answer commercial queries by directly nominating brands rat

Prompt Codebooks: Discrete Compositional Optimization for Language Model Instruction Refinement

arXiv:2605.28360v1 Announce Type: new Abstract: Automatic prompt optimization (APO) has driven significant gains in LLM-based agentic workflows. However, existing methods treat each task's prompt as a

PromptEmbedder:: Efficient and Transferable Text Embedding via Dual-LLM Soft Prompting

arXiv:2605.28066v1 Announce Type: cross Abstract: Large Language Models (LLMs) have demonstrated remarkable efficacy in text embedding, yet current adaptation methods like LoRA face significant bottle

Prompting Is All You Need: Multi-view Prompting Large Language Models for Aspect-Based Sentiment Analysis

arXiv:2605.28058v1 Announce Type: new Abstract: Recent work explored the capabilities of Large Language Models (LLMs) in Aspect-Based Sentiment Analysis (ABSA) through few-shot prompting, requiring su

ProvMind: Provenance-grounded reasoning for materials synthesis

arXiv:2605.28487v1 Announce Type: new Abstract: Materials process optimization requires reasoning over routes, conditions, tools and causal dependencies, yet most computational formulations flatten sy

PrunePath: Towards Highly Structured Sparse Language Models

arXiv:2605.28283v1 Announce Type: cross Abstract: Feed-forward networks (FFNs) dominate the parameter count and computation of modern language models, yet existing pruning methods often struggle to co

Pruning and Distilling Mixture-of-Experts into Dense Language Models

arXiv:2605.28207v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) is now the dominant architecture for frontier language models, yet it requires all expert parameters to be loaded in memory,

PubMedCausal: A Span-Level Annotated Corpus for Causal Relation Extraction in Biomedical Text

arXiv:2605.28363v1 Announce Type: new Abstract: Causal relation extraction (CRE) is central to biomedical text mining, but current resources often conflate causal relations with broader associations,

Qwen-Image-Bench: From Generation to Creation in Text-to-Image Evaluation

arXiv:2605.28091v1 Announce Type: new Abstract: Text-to-Image generation has evolved from basic image synthesis into a frequently used core capability in professional creative workflows, where simple

📢Qwen3.7-Max just hit #3 on ITbench-AA — a fresh benchmark testing how well models handle real-world enterprise IT tasks, agentic-style. 🔧…

📢Qwen3.7-Max just hit #3 on ITbench-AA — a fresh benchmark testing how well models handle real-world enterprise IT tasks, agentic-style. 🔧Agentic era, go with Qwen.🏃🏃 Artificial Analysis and IBM Resea

model-releasesqwen--x

RASR: Retrieval-Augmented Super Resolution for Practical Reference-based Image Restoration

arXiv:2508.09449v2 Announce Type: replace Abstract: Reference-based Super Resolution (RefSR) improves upon Single Image Super Resolution (SISR) by leveraging high-quality reference images to enhance t

REED: Post-Training Representation Editing for Cross-Domain Linguistic Steganalysis

arXiv:2605.28298v1 Announce Type: new Abstract: In real-world scenarios of linguistic steganalysis, tested texts usually come from unseen domains with different vocabularies, topics, writing styles, a

Reevaluating Policy Gradient Methods for Imperfect-Information Games

arXiv:2502.08938v4 Announce Type: replace Abstract: In the past decade, motivated by the putative failure of naive self-play deep reinforcement learning (DRL) in adversarial imperfect-information game

Reflective Dialogue between Teacher and Solver Agents for Video Question Answering

arXiv:2605.27885v1 Announce Type: new Abstract: Various approaches have been proposed to adapt Vision-Language Models (VLMs) to specialized domains for Video Question Answering, including fine-tuning

ReflexGrad: Within-Episode Failure Recovery in LLM Agents via Progress-Gated Dual-Process Routing

arXiv:2511.14584v3 Announce Type: replace-cross Abstract: We present ReflexGrad, a dual-process architecture for within-episode failure recovery in LLM agents without demonstrations. When agents commi

Regression Language Models for Code

arXiv:2509.26476v2 Announce Type: replace-cross Abstract: We study code-to-metric regression: predicting numeric outcomes of code executions, a challenging task due to the open-ended nature of program