All entries

What do Reward Models Memorize?

arXiv:2607.24484v1 Announce Type: cross Abstract: This paper studies what discriminatively trained reward models (RMs) memorize by measuring counterfactual memorization on two human preference dataset

researcharxiv-cs-cl

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

arXiv:2607.22781v1 Announce Type: cross Abstract: High task performance does not show whether a model retains prediction-relevant structural information in its internal representation. Temporal graph

researcharxiv-cs-ai

28 Jul 2026

Tutorials

When Activation Oracles Learn Not to Read: Concept-Specific Blind Spots in Fine-Tuned Oracles

arXiv:2607.23379v1 Announce Type: cross Abstract: Activation Oracles (AOs) are language models trained to answer natural-language questions about another model's internal activations. They offer a fle

tutorialsarxiv-cs-ai

When Can Depth Replace Precision? A Resource Theory of Quantized Neural Computation

arXiv:2607.23390v1 Announce Type: new Abstract: When can additional low-bit residual computation replace missing numerical precision for a fixed input-output map? We model a quantized residual system

When Can You Correct Distribution Drift in Temporal Graph Generation? A Sharpening--Drift Tension and an Impossibility for Observation-Based Correction

arXiv:2607.24662v1 Announce Type: new Abstract: Generative models of temporal graphs are trained on one stretch of an evolving network and deployed on the next, and they degrade badly in the gap. We s

When Every Simulation Counts: Value-Based Reinforcement Learning for Accelerated Photonics Inverse Design

arXiv:2607.23469v1 Announce Type: cross Abstract: Photonic-crystal surface-emitting lasers (PCSELs) can combine high-power operation with narrow-divergence surface emission, but optimizing coupled par

safetyarxiv-cs-ai

When Less Is More: A Controlled Benchmark of Lightweight CNNs for Satellite Land-Cover Segmentation on DeepGlobe

arXiv:2607.23024v1 Announce Type: new Abstract: High-resolution satellite imagery is the backbone of good land-cover classification, and without that, environmental monitoring, urban planning, and sus

When LLM Defenses Backfire: Characterizing Safety, Performance, and Cost Trade-offs

arXiv:2607.24392v1 Announce Type: cross Abstract: Jailbreak defenses are essential for protecting large language models (LLMs), but they can also introduce secondary costs that weaken model utility. W

When Low CER is Not Enough: An Analysis of Hallucinations in Vision-Language OCR Systems on Historical Uruguayan Documents

arXiv:2607.24077v1 Announce Type: new Abstract: Optical Character Recognition (OCR) is a key component in the digitization of historical archives. Recently, Vision-Language Models (VLMs) have emerged

When Rates Are Geometric: Rate-Certificate Transfer for Contact Splittings in Optimization

arXiv:2607.23642v1 Announce Type: cross Abstract: Discrete optimization algorithms are often analyzed through continuous-time limiting ODEs, but a convergence certificate for the ODE is not automatica

When Should Active RAG Retrieve? A Budget-Aware Evaluation of Utility, Calibration, and Cost

arXiv:2607.24010v1 Announce Type: new Abstract: Active RAG systems decide when to retrieve external knowledge during generation, making them a budget-sensitive case of agentic RAG and self-adaptive re

safetyarxiv-cs-lg

Where Is the Cost of Third-Party API Routers in Agentic Software Development?

arXiv:2607.23624v1 Announce Type: cross Abstract: Third-party API routers have become a common layer that unifies access across increasingly diverse LLM providers. In coding-agent workflows, high-auto

safetyarxiv-cs-ai

Where Quality Breaks in Compressed Short-Text Generation: Staged Bottleneck Localization

arXiv:2607.24176v1 Announce Type: new Abstract: Compressed short-text generators can fail in two different places: the codec may discard information before generation starts, or the latent generator m

applicationsarxiv-cs-cl

Which Models Perform Better in Inheritance Reasoning?

model-releasesarxiv-cs-cl

arXiv:2606.13751v4 Announce Type: replace Abstract: This paper presents the participation of team PSL in the QIAS 2026 Shared Task on Arabic Islamic inheritance reasoning. The task evaluates the abili

Which Workloads Belong in Orbit? A Workload-First Framework for Orbital Data Centers Using Semantic Abstraction

arXiv:2603.20317v2 Announce Type: replace Abstract: Space-based compute is becoming plausible as launch costs fall and data-intensive AI workloads grow. This paper proposes a workload-centric framewor

Who Gets Named: Citation Type Predicts Individual Naming by Grounded Language Models, and a Roster Instrument Captures 0.5% of It

model-releasesarxiv-cs-cl

arXiv:2607.23893v1 Announce Type: cross Abstract: Prior work on AI brand visibility measures the firm: does a model recommend a company, and does that track its reputation. This study asks the questio

Who Pays the Price? Stakeholder-Centric Prompt Injection Benchmarking for Real-world Web Agents

model-releasesarxiv-cs-ai

arXiv:2606.13385v2 Announce Type: replace-cross Abstract: LLM-based web agents are increasingly deployed in real-world settings such as e-commerce, where they interact extensively with untrusted web c

Why does Greedy Search produce Optimal Clustering Outcomes? A Fixed-Core Assignment Theory

arXiv:2607.24237v1 Announce Type: new Abstract: Many existing clustering methods are designed based on a set-oriented definition---a cluster is a set of similar points---relying a point-to-point simil

Wired for Overconfidence: A Mechanistic Perspective on Inflated Verbalized Confidence in LLMs

arXiv:2604.01457v3 Announce Type: replace Abstract: Large language models are often not just wrong, but confidently wrong: when they produce factually incorrect answers, they tend to verbalize overly

researcharxiv-cs-cl

WISERouter: LLM Routing with Workload Budget Constraint

arXiv:2607.23765v1 Announce Type: cross Abstract: Large language models (LLMs) achieve impressive performance across multiple domains, but using the most capable model for every query is prohibitive a

researcharxiv-cs-ai

WorldDiT: A Unified Diffusion Architecture for World and Action Modeling

arXiv:2607.23909v1 Announce Type: new Abstract: Many recent robot policies pursue stronger control by using large pretrained vision-language models (VLMs) as the action backbone. We introduce WorldDiT

Wrong Design Intent Is Worse Than None: A Derangement-Control Diagnosis of Header Conditioning in CAD Program Completion

arXiv:2607.23191v1 Announce Type: new Abstract: Fine-tuned code LLMs can be conditioned on a lightweight design-intent header to steer parametric CAD generation, but whether the model actually reads t

Hardware

X-Stage: An Overlooked Pipeline Stage for Communication-Computation Overlap in DiT Inference

arXiv:2607.23264v1 Announce Type: cross Abstract: Fine-grained, device-initiated communication lets persistent GPU kernels in distributed diffusion transformer (DiT) inference issue remote stores and

hardwarearxiv-cs-ai

XGRVFL-MV: Residual-Coupled Graph-Embedded Multi-View Random Vector Functional Link Network with FleXi Guardian Loss

arXiv:2607.23149v1 Announce Type: new Abstract: Random Vector Functional Link (RVFL) networks provide an efficient randomized learning framework for classification. Existing multi-view RVFL methods ut

XMatchAD: A Cross-Modal Matching Perspective on Reconstruction-based Anomaly Detection

arXiv:2607.23658v1 Announce Type: new Abstract: The remarkable success of reconstruction-based methods in Unsupervised Anomaly Detection (UAD) lies in their ability to identify and localize anomalies

XMix: Combating Extremely Noisy Labels via Local Smoothness in Self-Supervised Feature Space

arXiv:2607.23865v1 Announce Type: new Abstract: Supervised deep learning models rely on large, accurately labeled datasets, yet noisy annotations are often unavoidable and can severely degrade perform

xMIx: High-Performance Serving-Time Platform for Mechanistic Interpretability Apps

arXiv:2607.22595v1 Announce Type: new Abstract: Mechanistic interpretability (MI) has emerged as a powerful approach for analyzing and intervening in inference computations, with a growing number of a

safetyarxiv-cs-ai

You Talkin to Me?: A Network Analysis of Gendered Speaker-Addressee Patterns in Film Screenplays

arXiv:2607.22656v1 Announce Type: cross Abstract: Objective: This paper investigates the gendered structure of speaker addressee relationships in film dialogue, asking not merely who speaks, but who i

safetyarxiv-cs-cl

Zing: Social Mind for LLMs

model-releasesarxiv-cs-cl

arXiv:2607.23740v1 Announce Type: new Abstract: As large language models move from isolated task solving toward long-term service in human environments, they require social intelligence: the ability t

A Comparative Benchmark of Federated Learning Strategies for Mortality Prediction on Heterogeneous and Imbalanced Clinical Data

arXiv:2509.10517v3 Announce Type: replace Abstract: Machine learning can predict in-hospital mortality, but data privacy and the statistical heterogeneity of clinical data hamper its use. Federated Le

A Consensus-Based Framework for Relative Preference Evaluation of Large Language Models

arXiv:2607.21632v1 Announce Type: new Abstract: Traditional benchmarks for LLMs primarily rely on static datasets and objective scoring metrics, which often fail to capture differences in response qua

safetyarxiv-cs-cl

Local Ai

A Defense of the Quadratic Model

arXiv:2607.21716v1 Announce Type: new Abstract: Due to the complexity of neural network loss landscapes, optimization theory is forced to rely on idealized models, and there is generally a tradeoff be

local-aiarxiv-cs-lg

Local Ai

A Drift Stable Quantum Federated Learning for Intelligent Services

arXiv:2607.21647v1 Announce Type: new Abstract: Quantum federated learning enables distributed clients to train quantum neural networks without sharing local data, making it promising for privacy-awar

local-aiarxiv-cs-lg

A Dual Path Framework with Hotspot Guided Fusion for Three Dimensional CT to PET Synthesis in Head and Neck Cancer

arXiv:2607.21800v1 Announce Type: cross Abstract: 18F-FDG PET/CT plays a central role in staging, treatment planning, and response assessment for head and neck cancer by providing functional informati

A Factorial Study of Synthetic Data Generation for Low-Resource Machine Translation using Grammar Books

arXiv:2607.22376v1 Announce Type: new Abstract: Most endangered languages lack the parallel data required for machine translation, despite the existence of descriptive grammar books. We introduce a pi

researcharxiv-cs-cl

A Framework for Individual Tree Growth Reconstruction Using Multi-Platform Laser Scanning

arXiv:2607.22129v1 Announce Type: new Abstract: Accurate tree-level forest monitoring using laser scanning data requires reliable tree delineation, consistent tree correspondence across multitemporal

A Graph-Based Control Interface for Traffic Signals on Heterogeneous Road Networks

arXiv:2607.21831v1 Announce Type: new Abstract: We present a traffic-signal control interface in which a shared graph neural network assigns scores to individual traffic movements. Each junction conve

A Leakage-Free Stacked Ensemble Method for Multiclass Classification

arXiv:2607.22081v1 Announce Type: new Abstract: Multiclass classification is a fundamental problem across a wide range of domains. It is still challenging due to possession of high inter-class similar

A Monolithic Hand with Asymmetric Origami Bending and Dual-chamber Actuators

arXiv:2607.22320v1 Announce Type: new Abstract: The passive adaptability inherent in soft robotic hands affords them advantages in applications that require safe and compliant interaction. However, ex

applicationsarxiv-cs-ro

A Robust Pipeline for Differentially Private Federated Learning on Imbalanced Clinical Data using SMOTETomek and FedProx

arXiv:2508.10017v2 Announce Type: replace-cross Abstract: Federated Learning (FL) presents a groundbreaking approach for collaborative health research, allowing model training on decentralized data wh

applicationsarxiv-cs-lg

A Smooth Phase-Separation Model for Weak-Boundary Segmentation of Homogeneous Structures

arXiv:2607.22053v1 Announce Type: new Abstract: Segmentation of adjacent structures with similar intensity distributions remains a challenging problem in image analysis, particularly when object bound

A Unified Framework for Automated Assembly Sequence and Production Line Planning using Graph-based Optimization

arXiv:2512.13219v2 Announce Type: replace Abstract: This paper presents PyCAALP (Python-based Computer-Aided Assembly Line Planning), a framework for automated Assembly Sequence Planning (ASP) and Pro

applicationsarxiv-cs-ro

ACME: A Multi-Cultural, Multi-Embodiment Social-Navigation Dataset

arXiv:2607.21964v1 Announce Type: new Abstract: Understanding how robots and humans move in shared spaces is essential for designing effective social robot navigation policies and predicting human beh

researcharxiv-cs-ro

Agents

Action-Conditioned World Model for Goal Plane Probe Guidance in Robotic Ultrasound

arXiv:2607.21918v1 Announce Type: new Abstract: We present an action-conditioned world model framework for goal plane probe guidance in robotic ultrasound, with a focus on neck ultrasound scanning. Au

agentsarxiv-cs-ro

Agents

Active few-shot segmentation by reinforcing data selection

arXiv:2607.22371v1 Announce Type: new Abstract: Few-shot learning enables medical image segmentation models to adapt to new tasks using only a small number of labelled examples. However, adaptation pe

agentsarxiv-cs-cv

AdamNX: An Adam improvement algorithm based on a novel exponential decay mechanism for the second-order moment estimate

arXiv:2511.13465v5 Announce Type: replace Abstract: This paper studies the exponential decay mechanism of the second-moment estimate in Adam. We propose AdamNX and a time-varying second-moment decay r

Adaptive Contrast Enhancement and Optimised Feature Matching for RootSIFT-Based Palm-Vein Recognition

arXiv:2607.16077v2 Announce Type: replace Abstract: Palm-vein recognition is a highly secure biometric modality due to the uniqueness and subcutaneous nature of vein patterns. However, low contrast in

Agents

Adaptive Learned State Estimation based on KalmanNet

arXiv:2604.02441v2 Announce Type: replace Abstract: Hybrid state estimators that combine model-based Kalman filtering with learned components have shown promise on simulated data, yet their performanc

agentsarxiv-cs-ro