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PRISM: A Predictive Protocol for Permutation Optimization via Landscape Diagnostics

arXiv:2608.08344v1 Announce Type: cross Abstract: Permutation optimization arises whenever the components of a system are fixed but their ordering affects performance. We introduce PRISM, a predictive

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Research

PRISM-Delta: Differential Subspace Steering for Prompt Highlighting in Large Language Models

DGX agent

arXiv:2603.10705v2 Announce Type: replace Abstract: Prompt highlighting steers a large language model to prioritize user-specified text spans during generation. A key challenge of existing Key-editing

researcharxiv-cs-cl

11 Aug 2026

Privacy-Preserving Data Drift Detection and Recovery for Large-Scale LLM Applications via Proxy Representations

arXiv:2608.08245v1 Announce Type: cross Abstract: LLM applications deployed at scale face a fundamental challenge: privacy constraints prevent direct inspection of user interactions, making it difficu

Private Anytime Selective-Risk Certification for Federated Retrieval-Augmented Generation: Guarantees and Empirical Limits

arXiv:2608.07913v1 Announce Type: cross Abstract: Selective-risk certificates promise that accepted outputs meet a declared error target. We develop Fed-SRC, a score-agnostic certificate for federated

Local Ai

Private Etymology: Designing Relational Reuse of Shared Symbols in Long-Term Human-AI Interaction

arXiv:2608.08443v1 Announce Type: cross Abstract: Previous studies have shown that people can develop shared symbols, partner-specific expressions, personal idioms, inside jokes, and other parts of a

local-aiarxiv-cs-ai

Privileged Likelihood Is Not Automatically Value: Three Checks for Token Credit in On-Policy Self-Distillation

arXiv:2608.09263v1 Announce Type: new Abstract: Outcome verifiers score completed reasoning traces but do not assign credit to intermediate tokens. Privileged self-distillation attempts to fill this g

Privileged Solutions or Context-Induced Teacher Behavior? Dissecting On-Policy Self-Distillation

arXiv:2608.09228v1 Announce Type: cross Abstract: On-Policy Self-Distillation (OPSD) is commonly interpreted as the transfer of privileged information: a teacher observes the verified solution to the

Probabilistic Circuits for Knowledge Graph Completion with Reduced Rule Sets

arXiv:2508.06706v2 Announce Type: replace Abstract: Rule-based methods for knowledge graph completion provide explainable results, but often require tens of thousands of rules to achieve competitive p

ProbSPARQL: Querying Knowledge Graphs with Multi-dimensional, Uncertain Numeric Data

arXiv:2607.18262v2 Announce Type: replace Abstract: The SFB 1574 Circular Factory is building a shared knowledge graph infrastructure for integrating data about returned products. A central challenge

Progressive Learned Image Compression for Machine Perception

arXiv:2512.20070v2 Announce Type: replace Abstract: Recent advances in learned image codecs have extended from human perception toward machine perception However, progressive image compression with fi

applicationsarxiv-cs-cv

Projection-Retraction MPPI: Exact Constraint-Manifold Control for Manipulators

arXiv:2608.07573v1 Announce Type: new Abstract: Model Predictive Path Integral (MPPI) control is widely used in manipulation for its gradient-free, parallel handling of non-convex costs. Manipulation

researcharxiv-cs-ro

Prompt Embedding Probes (PEP): Hallucination Detection in LLMs from Hidden States

arXiv:2608.08024v1 Announce Type: cross Abstract: Large language models (LLMs) can generate fluent and useful responses but remain prone to hallucinations. We introduce Prompt Embedding Probes (PEP),

Prompt engineering does not universally improve Large Language Model performance across clinical decision-making tasks

model-releasesarxiv-cs-cl

arXiv:2512.22966v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated promise in medical knowledge assessments, yet their practical utility in real-world clinical decision

ProPINN: Demystifying Propagation Failures in Physics-Informed Neural Networks

arXiv:2502.00803v3 Announce Type: replace Abstract: Physics-informed neural networks (PINNs) have earned high expectations in solving partial differential equations (PDEs), but their optimization usua

PROSLEX: A Novel Dataset for Expert-Annotated Legal Statute Prediction for Indian Judiciary

arXiv:2608.08830v1 Announce Type: new Abstract: Legal Statute Prediction (LSP) involves automatically identifying relevant legal statutes given factual descriptions in legal documents, typically frame

Protecting patient privacy in clinical foundation models: Technical and legal perspectives

arXiv:2608.07705v1 Announce Type: new Abstract: Clinical foundation models trained on large-scale patient data are increasingly used for decision support, screening, and public health. As deployment e

applicationsarxiv-cs-ai

Proxy OPD: On-Policy Distillation with Transferable Relative Proxy Update

arXiv:2607.11505v2 Announce Type: replace-cross Abstract: Post-training for large language models typically couples policy exploration with model optimization, hindering the reuse of high-reward behav

Quality-Diversity Stress Tests for Process Reward Models:What Archive Coverage Can and Cannot Certify

arXiv:2608.08008v1 Announce Type: new Abstract: Process reward models (PRMs) score intermediate reasoning steps and are widely used for search, ranking, and training, but optimization can exploit thes

Quantifying Membership Disclosure Risk for Tabular Synthetic Data Using Kernel Density Estimators

arXiv:2603.10937v2 Announce Type: replace Abstract: The use of synthetic data has become increasingly popular as a privacy-preserving alternative to sharing real datasets, especially in sensitive doma

applicationsarxiv-cs-lg

Quantization Degradation in Large Language Models: A Signal-Noise Perspective

arXiv:2608.08188v1 Announce Type: new Abstract: Post-training quantization reduces the deployment cost of large language models, yet how severely a quantized model degrades is not determined by bit-wi

Agents

QuantumMind: Constraint-Grounded Agentic Reasoning for Speedup Analysis in Quantum Computing

arXiv:2608.07743v1 Announce Type: new Abstract: Identifying a meaningful quantum speedup requires more than matching a classical problem to a familiar quantum primitive: the claim must preserve the ta

agentsarxiv-cs-ai

QuArch: A Benchmark for Evaluating LLM Reasoning in Computer Architecture

arXiv:2510.22087v3 Announce Type: replace-cross Abstract: The field of computer architecture, which bridges high-level software abstractions and low-level hardware implementations, remains absent from

Agents

Query-Only Backdoor Attacks on Self-Evolving Skills via Trajectory Poisoning

arXiv:2608.08303v1 Announce Type: new Abstract: Agentic skills improve large language model (LLM) agents by encoding reusable procedures for complex tasks. However, manually authored skills often adap

agentsarxiv-cs-ai

Quokka: Accelerating Program Verification with LLMs via Invariant Synthesis

arXiv:2509.21629v4 Announce Type: replace-cross Abstract: Program verification relies on loop invariants, yet automatically discovering strong invariants remains a long-standing challenge. We investig

R3S: Refining and Recovering Reinforcement Signals for Multilingual Understanding and Reasoning

arXiv:2602.05940v2 Announce Type: replace Abstract: Large reasoning models often default to English reasoning when processing non-English questions, yet their performance drops substantially when reas

researcharxiv-cs-cl

RA-FinBERT: Rule-aware LoRA adaptation for low-resource financial sentiment classification

model-releasesarxiv-cs-cl

arXiv:2608.09834v1 Announce Type: new Abstract: Financial sentiment analysis converts unstructured financial news into quantitative signals that can support market analysis and decision-making. Existi

RAG-3DSG: Enhancing 3D Scene Graphs with Re-Shot Guided Retrieval-Augmented Generation

arXiv:2601.10168v3 Announce Type: replace-cross Abstract: Open-vocabulary 3D Scene Graph (3DSG) can enhance various downstream tasks in robotics by leveraging structured semantic representations, yet

applicationsarxiv-cs-ai

RAG-Audio: Retrieval-Augmented Generation for Faithful Brain-to-Audio Reconstruction

arXiv:2608.09331v1 Announce Type: cross Abstract: Brain-to-audio reconstruction is limited by prior domination: when a pretrained generator is conditioned on a weak neural signal, it produces realisti

RAG-Based Auto-Configuration for Industrial Fieldbus Devices

arXiv:2608.08618v1 Announce Type: cross Abstract: Industrial device commissioning requires engineers to manually extract hundreds of protocol-specific parameters from heterogeneous PDF manuals and tra

RAGMesh with FaME-G2E: Long-Form Text-Driven 3D Face Generation and Editing

model-releasesarxiv-cs-cv

arXiv:2608.09186v1 Announce Type: new Abstract: Text-driven 3D face generation and editing remains challenging due to the difficulty of translating long-form descriptions into fine-grained facial geom

Agents

RangeFactory: Scalable Construction of Multi-Hop Cyber Ranges

arXiv:2608.09526v1 Announce Type: cross Abstract: Real-world cyberattacks often require sustained progress across multiple hosts and network segments, making multi-hop cyber ranges essential infrastru

agentsarxiv-cs-ai

RankGuide: Tensor-Rank-Guided Routing and Steering for Efficient Reasoning

arXiv:2604.16694v2 Announce Type: replace Abstract: Large reasoning models (LRMs) enhance problem-solving capabilities by generating explicit multi-step chains of thought (CoT) reasoning; however, the

RAVEN-Eval: Rubric-Guided Automatic Evaluation for AI Video Generation Models Based on LMM Preference Judgement

arXiv:2608.09111v1 Announce Type: new Abstract: AI video generation has advanced rapidly and entered widespread commercial use. As a result, quality differences among videos produced by state-of-the-a

RAVEN: Frozen Random Graph Reservoirs with Physics-Informed Interaction Fingerprints for Protein-Ligand Binding Affinity Prediction

arXiv:2608.09099v1 Announce Type: new Abstract: Quantitative estimation of protein-ligand binding affinity from three-dimensional complex structures is a fundamental task in structure-based computatio

Local Ai

RayLift: Lifting Complementary Ray-Wise Evidence with 3D Geometry Priors for Semantic Scene Completion

arXiv:2608.08476v1 Announce Type: new Abstract: Camera-based 3D semantic scene completion (SSC) provides comprehensive scene understanding for autonomous driving and robotics. However, existing method

local-aiarxiv-cs-cv

Reading Cognition as Decisions Unfold in Words: A Factorized Inverse Decision Model

arXiv:2608.09222v1 Announce Type: new Abstract: Inverse decision modeling infers latent properties of decision processes from observed behavior, but existing formulations rely primarily on action traj

applicationsarxiv-cs-cl

Reading is not Reasoning: Bridging the Agentic Policy Gap in Vision-Text Compression

arXiv:2608.08960v1 Announce Type: new Abstract: Multi-step language-model agents repeatedly process growing interaction histories, leading to substantial context costs. Vision--text compression reduce

Readout-Rank Laws for Isotropic Quantum Tangents

model-releasesarxiv-cs-lg

arXiv:2608.07628v1 Announce Type: cross Abstract: Deep parameterized quantum circuits may remain sensitive to a parameter change while the observables retained by a learning model barely respond. We s

Real Data Closes Synthetic-to-Real Gap in Optical Chemical Structure Recognition

model-releasesarxiv-cs-cv

arXiv:2608.09100v1 Announce Type: cross Abstract: Millions of chemical structures appear in patents and papers only as drawings, and using that information at scale requires reading the drawings. OCSR

Real-Time Climate Risk Assessment for Supply Chain Resilience: A Data-Driven Nowcasting Framework for Colombian Agriculture

arXiv:2608.09846v1 Announce Type: new Abstract: This paper presents a methodological framework for real-time climate risk assessment using data-driven nowcasting techniques to enhance supply chain res

applicationsarxiv-cs-lg

Real-Time Nonlinear MPC via Sequential Quadratic Programming with Structure-Exploiting ADMM and Interior-Point Methods for Underactuated Double-Pendulum Swing-Up

arXiv:2608.09272v1 Announce Type: cross Abstract: The 4th 'AI Olympics with RealAIGym' competition, to be held at IJCAI-ECAI 2026 in Bremen, challenges participants to develop a global control policy

safetyarxiv-cs-ro

Hardware

Real-time physics inversion for retrieval of sub-pixel wildfire temperatures from VSWIR imaging spectroscopy

arXiv:2608.07580v1 Announce Type: new Abstract: In this work, we present a wildfire temperature retrieval framework for VSWIR imaging spectroscopy data, employed on data from NASA's Airborne Visible I

hardwarearxiv-cs-cv

RealDenseFace: Real-time Monocular 3D Face Reconstruction from Dense UV-space Priors

model-releasesarxiv-cs-cv

arXiv:2608.09238v1 Announce Type: new Abstract: Recent monocular 3D face reconstruction methods achieve high fidelity by fitting a 3D Morphable Model (3DMM) to dense priors predicted by networks, but

Reason Wide, Not Deep: Amortizing the Reasoning Premium into Distilled Skills

arXiv:2608.07885v1 Announce Type: new Abstract: Reasoning modes of language models outperform their non-reasoning counterparts on multi-step agentic tasks, but pay a 3-6x premium in output tokens on e

Reconfigurable Structural Robotic Assembly: Interlocking 3D Aggregations with Self-Aligning Compound Nested Lattice Modules

arXiv:2608.07576v1 Announce Type: new Abstract: Robotic construction systems often treat the material system and the robot as separate design problems, locating intelligence primarily in hardware, sen

safetyarxiv-cs-ro

RecoverFly: A Failure-Aware Reinforcement Learning Post-Training Framework for Aerial Vision-Language Navigation

arXiv:2608.09467v1 Announce Type: cross Abstract: Unmanned aerial vehicle vision-language navigation (UAV-VLN) requires agents to translate visual observations and language instructions into reliable

Recurrent Neural Networks Beyond Time: Learning from Multiple Ordered Projections

arXiv:2608.09690v1 Announce Type: new Abstract: Recurrent neural networks (RNNs) are widely used for sequence learning, yet their application is commonly associated with temporal data, although recurr

Reducing Pretraining-Generation Mismatch in Diffusion Language Models

model-releasesarxiv-cs-cl

arXiv:2608.09424v1 Announce Type: new Abstract: Autoregressive language models align training and use: generation conditions on a clean prompt, and training predicts future tokens from clean left cont