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Context Assembly as the Controlled Variable: A Control-Theoretic View of Harness Policies for Frozen LLM Agents

arXiv:2607.25408v1 Announce Type: new Abstract: A growing body of 2026 work applies control theory to LLM agents: Lyapunov-certified stability for tool-mediated controllers (Prinos et al., 'Stable Age

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Contextual Deconvolution for Variance-Stable Demand Sensing: Kernel-Modulated Operators in Promotional Retail

DGX agent

arXiv:2607.25664v1 Announce Type: new Abstract: Machine learning demand forecasts optimize statistical accuracy yet leave excess operational volatility that inflates safety stock and amplifies the Bul

safetyarxiv-cs-lg

29 Jul 2026

ContractHIL-HLS: Contract-Aligned Multi-Agent Workflow with Hardware-in-the-Loop Feedback for HLS Design

arXiv:2607.25283v1 Announce Type: new Abstract: This paper presents ContractHIL-HLS, a contract-aligned multi-agent workflow for practical high-level synthesis (HLS) engineering. The workflow makes th

Contrastive Weak-to-strong Generalization

arXiv:2510.07884v3 Announce Type: replace-cross Abstract: Weak-to-strong generalization provides a promising paradigm for scaling large language models (LLMs) by training stronger models on samples fr

CoRT: Counterfactual Replay for Token-Level Rubric-Guided Policy Optimization

arXiv:2607.25659v1 Announce Type: new Abstract: Rubric-based reinforcement learning enriches language model training by evaluating model outputs against explicit criteria. Yet in GRPO-style pipelines,

Data-Dependent Regret and Polyak Corrections for Constrained Online Convex Optimization

arXiv:2607.25480v1 Announce Type: new Abstract: Constrained online convex optimization requires minimizing regret against adversarial convex costs while satisfying a convex constraint at every round,

Dataset Poisoning Attacks on Behavioral Cloning Policies

arXiv:2511.20992v2 Announce Type: replace Abstract: Behavior Cloning (BC) is a popular framework for training sequential decision policies from expert demonstrations via supervised learning. As these

DDSNet: Dual-domain Symmetry-aware Network for PCSEL Property Prediction

arXiv:2607.24785v1 Announce Type: cross Abstract: Efficient exploration of the photonic crystal (PhC) lattice design space is essential for developing photonic crystal surface-emitting lasers. While c

Decentralized Scalable Exploration via Emergent Adaptive Levy Walks on Minimal-Sensing Platforms

arXiv:2607.25195v1 Announce Type: new Abstract: Efficient autonomous exploration with palm-sized nano-UAVs remains challenging due to severe limitations in sensing, computation, and flight endurance.

DensFiLM: Density-Conditioned Video Saliency for Crowd Scenes

arXiv:2607.25465v1 Announce Type: new Abstract: Video saliency models typically apply a single fixation strategy across crowd scenes, despite systematic changes in attention with crowd density. Sparse

Do Models Fake Alignment Without Clear Consequences?

arXiv:2607.24758v1 Announce Type: new Abstract: Large language models are capable of recognizing evaluation contexts and altering their behavior to reflect evaluator expectations rather than typical d

Does Runtime Topology Context Improve LLM-Generated Kubernetes Security Patches?

arXiv:2607.25995v1 Announce Type: cross Abstract: Kubernetes is central to the cloud-native ecosystem, orchestrating containerised workloads. Recent work suggests that large language models (LLMs) can

DSCD-Nav: Dual-Stance Cooperative Debate for Object Navigation

arXiv:2601.21409v3 Announce Type: replace Abstract: Adaptive navigation in unfamiliar indoor environments is crucial for household service robots. Despite advances in zero-shot perception and reasonin

Early Detection of Distributed Backdoors in Multi-Agent LLM Systems: A Characterization Study

arXiv:2607.24893v1 Announce Type: cross Abstract: Multi-agent LLM systems can be attacked by a payload that no single agent ever holds in full: a poisoned tool hides encrypted fragments in its observa

Egocentric Station Holding of Robotic Fish in Unknown Turbulent Background Flow

arXiv:2607.24860v1 Announce Type: new Abstract: Approaching a target position and holding station in flowing water is a fundamental and critical capability for robotic fish operating in natural aquati

Evaluation of Adversarial Robustness in Arabic Language Models

arXiv:2607.25814v1 Announce Type: new Abstract: The emergence of the recent outstanding capabilities of Arabic Language Models has opened doors for exposing their vulnerabilities. One of the major sec

safetyarxiv-cs-cl

Evaluation of forced alignment of code-mixed speech: the case of Hindi-English

arXiv:2607.25581v1 Announce Type: new Abstract: Code-mixed speech poses unique challenges to forced alignment: expanded inventories, orthographic errors, and speaker variation. We evaluate forced alig

safetyarxiv-cs-cl

Explanation-Bound Tool Execution for AI Agents: Server-Verified Action Claims Without Trusting Model Rationales

arXiv:2607.25364v1 Announce Type: new Abstract: Tool-using agents expose structured calls but commonly attach free-form rationales. Such rationales are neither authorization nor reliable introspection

Face De-Identification: A Domain-Centric Survey from Capture to Processing

arXiv:2607.25926v1 Announce Type: cross Abstract: Face de-identification (De-ID) aims to remove or conceal personally identifiable facial features in images or videos to prevent identity recognition w

Faces of Fairness: Examining Bias in Facial Expression Recognition Datasets and Models

arXiv:2502.11049v3 Announce Type: replace Abstract: Automated Facial Expression Recognition (FER), involves two critical aspects: data and model design. Both significantly influence bias and fairness

Fairness Is Not Enough: Auditing Competence and Intersectional Bias in AI-powered Resume Screening

arXiv:2507.11548v3 Announce Type: replace-cross Abstract: The use of publicly available generative AI systems for resume evaluation is often justified by the assumption that these tools reduce bias re

Falling Behind Drives Unsafe Development in an Idealised AI Race Experiment

arXiv:2607.26034v1 Announce Type: new Abstract: Technological races create tension between speed and safety: actors may gain by moving faster than competitors, even when risky development is harmful.

Fine-Grained Food Image Understanding via Target-Aware Data Alignment

arXiv:2607.25794v1 Announce Type: new Abstract: Fine-grained food visual--semantic understanding requires models to capture subtle distinctions across ingredients, cooking methods, doneness, color, te

From Dyad to Triad: Eliciting XAI Requirements in Stroke Rehabilitation

arXiv:2607.25423v1 Announce Type: cross Abstract: Eliciting explainable AI (XAI) requirements from stroke survivors presents a methodological challenge with direct implications for the design of trust

@GaryMarcus OpenAI and Anthropic desperately need to raise prices. We seem to be faced with one of three choices for them: 1. Bailout 2. Ban…

Gary Marcus has argued that both OpenAI and Anthropic must increase their pricing, citing the rapid decline in token costs and competition from open‑source models. He presents a binary choice: either

safetygary-marcus--x

Group Equivariant Diffusion for Anomaly Detection in Computational Cytology

arXiv:2607.25503v1 Announce Type: new Abstract: Computational cytology on whole-slide images is challenging because malignant cells are rare, heterogeneous, and annotated slides are scarce. Anomaly de

Guardians and Offenders: A Survey on Harmful Content Generation and Safety Mitigation of LLM

arXiv:2508.05775v3 Announce Type: replace Abstract: Large Language Models (LLMs) have revolutionized content creation across digital platforms, offering unprecedented capabilities in natural language

safetyarxiv-cs-cl

Handy dandy AI crisis flowchart from @klonick

Gary Marcus shared a “handy dandy AI crisis flowchart” created by Kate Klonick (@Klonick) on Saturday, July 28. The tweet also notes that he had planned to write an article about Hugging Face and Open

safetygary-marcus--x

Hybrid Analysis for Secure MCP Tool Use in LLM Agents

arXiv:2607.25297v1 Announce Type: cross Abstract: The rapid development of large language model (LLM) agents has enabled their broad adoption across diverse real-world tasks. To standardize interactio

Improving Rare Medication Recommendation with Counterfactual Data Augmentation and Large Language Models

arXiv:2607.24829v1 Announce Type: cross Abstract: AI-based medication recommendation systems have attracted substantial attention due to their potential to enhance patient safety and therapeutic outco

Interpretable GOHR Agents via Sparse Autoencoders

arXiv:2607.25132v1 Announce Type: new Abstract: A central challenge in interpreting learned decision-making systems is to determine whether their internal representations contain concepts that help ex

Inverse RL Helps Align AI by Imitating Humans

arXiv:2607.24900v1 Announce Type: new Abstract: Language model alignment aims to make model behavior reliably reflect desirable properties such as helpfulness, safety, and instruction following. Curre

IRIS: Reusable Identity Representations from Frozen LLMs for Entity Alignment

arXiv:2607.25579v1 Announce Type: cross Abstract: Entity alignment (EA) identifies entities across knowledge graphs (KGs) that refer to the same real-world object. Conventional EA methods mainly explo

Keypoint-Guided Optimal Transport: Models, Algorithms, and Applications

arXiv:2303.13102v2 Announce Type: replace Abstract: Existing Optimal Transport (OT) methods mainly derive the optimal transport plan/matching under the criterion of transport cost/distance minimizatio

Large Language Model for Operations Research Formulation Selection in Multi-Warehouse Inventory Allocation

arXiv:2607.25956v1 Announce Type: new Abstract: Multi-warehouse inventory allocation is typically formulated as a mixed-integer programming (MIP) problem, yet no single formulation consistently matche

Learning from Local Walks on Dynamic Graphs with Bandit Feedback

arXiv:2607.10571v2 Announce Type: replace-cross Abstract: We study stochastic multi-armed bandits on dynamic graphs, where arms correspond to the vertices of a network with time-varying edges. In this

Learning from the Unseen: Offline Reinforcement Learning with Hidden Actions

arXiv:2607.25241v1 Announce Type: cross Abstract: Standard offline reinforcement learning (RL) algorithms typically assume that the actions in the dataset are observed without error. However, in many

LGFNet: A CTC-Guided Local-Global Fusion Framework for Single-Channel Sleep Staging

arXiv:2607.25197v1 Announce Type: new Abstract: Sleep staging remains challenging due to long-range temporal dependencies, ambiguous stage transitions-particularly in N1-and substantial distribution s

LLM as Forecasting Planner: Training-Free Text Conditioning for Time-Series Foundation Models

arXiv:2607.24892v1 Announce Type: cross Abstract: Text-conditioned time-series forecasting predicts a series from both its numerical history and natural-language context, allowing forecasts to account

LLM Scheming Inversely Scales with Pretraining Language Coverage

arXiv:2607.24769v1 Announce Type: new Abstract: With the growing capabilities of frontier models, AI alignment becomes increasingly critical in high-risk deployment settings. While recent work has emp

Med-SegLens: Latent-Level Model Diffing for Interpretable Medical Image Segmentation

arXiv:2602.10508v2 Announce Type: replace Abstract: Modern segmentation models achieve strong predictive performance but remain largely opaque, limiting our ability to diagnose failures, understand da

Medical world models in healthcare: foundations, applications, and challenges for trustworthy clinical translation

arXiv:2607.25242v1 Announce Type: new Abstract: Medical world models offer a framework for extending medical artificial intelligence beyond static prediction by representing evolving patient states an

Motion-Acceleration Calibration and Compensation in IMUs without External Equipment for Attitude Estimation Filters

arXiv:2607.25784v1 Announce Type: new Abstract: Attitude estimation based on inertial sensing requires measurements of local angular velocities and local gravity via gyroscopes and accelerometers. How

Motion Generation With Environmental Constraints

arXiv:2607.25053v1 Announce Type: new Abstract: Robot motion planning faces challenges in high-dimensional spaces and uncertain environments, often constrained by the need for collision-free motions.

Multi-Sensor Alignment for Weather Simulations

arXiv:2607.25612v1 Announce Type: new Abstract: Perception tasks for autonomous vehicles need to work satisfactorily in adverse weather conditions. Due to lack of real-world weather datasets, weather

NEXT: Reasoning-Driven Video Recommendation via a Vision-Language Model

arXiv:2607.24789v1 Announce Type: cross Abstract: We present NEXT (Next-interest EXploration Transformer), a reasoning-driven video recommendation framework that reasons over the video a user has just

ODYSSE: Episode-wise Policy Optimization for Personalized Agentic Reasoning

arXiv:2607.25369v1 Announce Type: new Abstract: Agentic systems have rapidly advanced in their ability to interact with real-world environments, leverage external tools, and provide services for users

On the Use of Synthetic Data for Threshold Calibration in Face Recognition: Performance and Security Implications for Border Control Systems

arXiv:2607.25990v1 Announce Type: new Abstract: The recently deployed Entry/Exit System (EES) introduces large-scale biometric verification into European border control, requiring face recognition sys