Search: “evaluation”

Safin-1: Safety from Within through Memory-Native State Evolution

arXiv:2609.00092v1 Announce Type: new Abstract: Long-horizon complex tasks require foundation models to accumulate information, maintain internal states, and adapt over extended interactions. Safety s

safetyarxiv-cs-lg

Agents

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Scientific Agent Skills: A Library of Procedural Knowledge for Research Agents

DGX agent

arXiv:2609.00065v1 Announce Type: cross Abstract: A language-model agent asked to analyse an experiment will usually return working code. Whether the analysis is defensible is a different question. A

agentsarxiv-cs-ai

2 Sept 2026

SciTrue: Reliable Scientific Claim Validation with Frontier and Open Language Models at the NTCIR SciClaimEval Task

arXiv:2609.00654v1 Announce Type: new Abstract: We describe the SciTrue team's participation in both subtasks of the NTCIR-19 SciClaimEval task~ite{sciclaimeval}, which asks systems to verify scientif

Selective Agent Guidance via Entropy: Learning Autonomous Policies from Imperfect VLM Teachers

arXiv:2609.01567v1 Announce Type: new Abstract: Vision-Language Models (VLMs) provide useful priors for interactive decision-making, but using them directly as policies is expensive and brittle: they

Semantic-Guided Multimodal Preprocessing for Vision Transformer-Based Clear Cell Renal Cell Carcinoma Grading

arXiv:2609.01426v1 Announce Type: cross Abstract: Clear cell renal cell carcinoma (CCRCC) grading is essential for treatment planning, yet existing approaches either analyze patch-level images directl

Semi-Supervised Biomedical Image Segmentation via Diffusion Models and Teacher-Student Co-Training

arXiv:2504.01547v3 Announce Type: replace Abstract: Supervised deep learning achieves strong performance in biomedical image segmentation but relies on costly pixel-wise annotations, motivating semi-s

Socrates went Nuclear: Comparing Interaction Strategies for AI systems in a Learning Context using Brain Sensing

arXiv:2609.00584v1 Announce Type: new Abstract: Does unrestricted AI access bypass the cognitive effort required for learning, or does it streamline knowledge acquisition? This paper reports on a stud

Some Emotions Run Deeper: Layer-wise Probing and Causal Intervention in Large Language Models

arXiv:2609.01279v1 Announce Type: cross Abstract: Emotion is expressed in text along a wide spectrum, from surface lexical cues to inferences entangled with content. Most layer-wise analyses of emotio

Sources of Truth: A Multi-Platform, Multilingual Audit of Citations in AI Mental Health Information Queries

arXiv:2609.00319v1 Announce Type: cross Abstract: Online health information seeking is shifting from keyword search, where users consider a ranked list of links, to conversational systems that compose

Spatial Autoregressive Modeling of DINOv3 Embeddings for Unsupervised Anomaly Detection

arXiv:2603.02974v2 Announce Type: replace Abstract: DINO models provide rich patch-level representations that have recently enabled strong performance in unsupervised anomaly detection (UAD). Most exi

SpecMind: Enabling Spectrum Intelligence via Multi-Agent Hybrid Retrieval-Augmented Generation

arXiv:2609.00427v1 Announce Type: new Abstract: The exponential growth of wireless devices is driving unprecedented spectrum demand, pushing spectrum management toward more fine-grained decisions acro

Spiking Patches: Asynchronous, Sparse, and Efficient Tokens for Event Cameras

arXiv:2510.26614v2 Announce Type: replace Abstract: We propose tokenization of events and present a tokenizer, Spiking Patches, specifically designed for event cameras. Given a stream of asynchronous

researcharxiv-cs-cv

SpokenUS: A Spoken User Simulator for Task-Oriented Dialogue

arXiv:2603.16783v2 Announce Type: replace Abstract: Robust voice agents require exposure to the full diversity of how people interact through speech. However, obtaining enough spoken interactions is p

Staged Linguistic Seeding: Grounded Query Expansion for Verified-Unit QA in AI Contact Centers

model-releasesarxiv-cs-cl

arXiv:2609.00844v1 Announce Type: new Abstract: Customer-service QA in an AI contact center (AICC) runs under deployment constraints that benchmark QA misses: tight voice-hotline latency and a high co

StainPresetNet: Stain Preset Network for Fast Multi-to-Multi Stain Normalization

arXiv:2609.01146v1 Announce Type: cross Abstract: Stain normalization reduces color variations caused by variations in staining protocols and imaging conditions, thereby enhancing computer-aided diagn

Stochastic Optimization of Tree Tensor Networks

arXiv:2609.00870v1 Announce Type: cross Abstract: Tensor networks, originally developed for quantum many-body physics, are promising models for machine learning. We derive stochastic Riemannian optimi

StudentSim: Training LLM-based Student Simulators

model-releasesarxiv-cs-cl

arXiv:2609.01591v1 Announce Type: new Abstract: AI tutors are most useful when they adapt to each student's strengths, weaknesses, and preferred guidance, but evidence about which guidance works for w

Subspace Levenberg Marquardt Algorithms in Training Neural Networks

arXiv:2609.00789v1 Announce Type: new Abstract: The Levenberg-Marquardt (LM) algorithm is a well-known second-order method for rapid convergence and strong robustness when training small- to medium-si

researcharxiv-cs-lg

Subword Segmental BabyLMs: Learning to Tokenise for Sample-Efficient Pretraining

arXiv:2609.01151v1 Announce Type: new Abstract: In the standard LM training pipeline, subword tokenisation is applied as a preprocessing step. Subword segmental language modelling is an alternative pa

safetyarxiv-cs-cl

SupraTok: Cross-Boundary Tokenization for Enhanced Language Model Performance

arXiv:2508.11857v3 Announce Type: replace-cross Abstract: Tokenization remains a persistent bottleneck in language modeling, especially when vocabulary learning is limited by whitespace boundaries. We

TacVLA: Contact-Aware Tactile Fusion for Robust Vision-Language-Action Manipulation

arXiv:2603.12665v3 Announce Type: replace Abstract: Vision-Language-Action (VLA) models have demonstrated significant advantages in robotic manipulation. However, their reliance on vision and language

safetyarxiv-cs-ro

Hardware

Text Capability Loss in Vision-Language Adaptation: An Attention-Sink Diagnosis

arXiv:2609.00746v1 Announce Type: new Abstract: Fine-tuning a pretrained LLM into a vision-language model (VLM) can erode the backbone's text capability, with the damage concentrated on tasks that req

hardwarearxiv-cs-lg

Applications

The Privacy-Hallucination Tradeoff in Differentially Private Language Models

arXiv:2609.00492v1 Announce Type: new Abstract: Both privacy and factual accuracy are paramount in high-stakes domains like healthcare. Concerningly, we uncover and investigate a privacy-hallucination

applicationsarxiv-cs-ai

Tutorials

The Structure of Quantization Damage in LLMs: Why the Next Bit Should Be Spent Globally

arXiv:2609.01587v1 Announce Type: cross Abstract: Post-training quantization (PTQ) is widely used to reduce the cost of serving large language models (LLMs), but its accuracy cost is uneven and is oft

tutorialsarxiv-cs-cl

TopoAlign: A Framework for Aligning Code to Math via Topological Decomposition

arXiv:2510.11944v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) excel at both informal and formal (e.g. Lean 4) mathematical reasoning but still struggle with autoformalisation,

Towards Agentic Cloud Engineering: Graph and Loop Engineering with a Zero-Trust Agent Harness

arXiv:2609.00050v1 Announce Type: cross Abstract: Agentic AI is enabling cloud-based workflows in which autonomous agents reason over operational state, invoke authorized tools, modify software and in

Towards Provable and Scalable Training of Quantized Neural Networks with Ising Optimization

arXiv:2506.18240v5 Announce Type: replace-cross Abstract: Training quantized neural networks remains fundamentally challenging due to non-convex loss landscapes and discrete parameter spaces. We intro

Training-Free Policy Violation Detection via Activation-Space Whitening in LLMs

arXiv:2512.03994v4 Announce Type: replace Abstract: As organizations increasingly deploy LLMs in sensitive domains such as legal, financial, and medical settings, ensuring alignment with internal orga

safetyarxiv-cs-lg

UI-Venus-2 Technical Report

arXiv:2609.00028v1 Announce Type: new Abstract: Multimodal GUI agents have emerged as a promising paradigm for digital task automation, yet transitioning from benchmark-oriented models to dependable r

UI-VISA: U-Net Initialized Vascular Image Segmentation Architecture

arXiv:2609.01598v1 Announce Type: new Abstract: Accurate segmentation of vascular structures in digital subtraction angiography (DSA) images remains challenging due to the thin, elongated, and branchi

researcharxiv-cs-cv

Uncovering and Mitigating Aggregation-Induced Reward Hacking in Multi-Reward Reinforcement Learning

arXiv:2609.00213v1 Announce Type: new Abstract: Reinforcement learning fine-tuning of large language models increasingly adopts multiple reward dimensions, including verifiable rules, task-specific ev

safetyarxiv-cs-cl

Value Over Language Model: Detecting Original Contribution in Writing

arXiv:2609.00700v1 Announce Type: new Abstract: LLMs have been rapidly adopted across writing tasks, prompting the development of tools for detecting LLM-generated text. Yet, these tools largely measu

Local Ai

VATO: A Vortex-Force-Aware Transformer Operator for Unsteady Separated Aerofoil Flows

arXiv:2609.00507v1 Announce Type: new Abstract: Accurate prediction of unsteady separated flows is challenging because the aerodynamic loads depend on nonlinear separation and vortex-shedding dynamics

local-aiarxiv-cs-lg

VectorGym: A Multi-Task Benchmark for SVG Code Generation, Sketching and Editing

arXiv:2603.29852v2 Announce Type: replace-cross Abstract: We introduce VectorGym, a comprehensive benchmark suite for Scalable Vector Graphics (SVG) that spans generation from text and sketches, compl

Agents

Vision-Language-Guided Pseudo-Labels for Unsupervised Domain Adaptation in Semantic Segmentation for Waste Sorting

arXiv:2609.00898v1 Announce Type: cross Abstract: Obtaining labeled data for semantic segmentation in applied settings (e.g., autonomous driving, industrial waste sorting) is expensive and often infea

agentsarxiv-cs-ai

Local Ai

Visual Attention Faithfulness in Vision-Language Models is Heterogeneous

arXiv:2609.00830v1 Announce Type: cross Abstract: Whether attention weights faithfully reflect model reasoning has been actively debated in NLP, yet this question remains largely unexplored for the vi

local-aiarxiv-cs-ai

ViTAL-X: Video-Text Alignment with Cross-Modal Temporal Edits

arXiv:2609.00505v1 Announce Type: new Abstract: Video-text models adapted from image-text architectures (e.g., CLIP) frequently exhibit temporal blindness, the inability to perceive fundamental cues l

When Compression Helps and When It Hurts: Condition-Aware Analysis of Chain-of-Thought Distillation

arXiv:2606.21704v2 Announce Type: replace Abstract: Chain-of-Thought (CoT) distillation transfers multi-step reasoning from large reasoning models to smaller students, but verbose teacher traces infla

When Features Become Instances: Inverted Contrastive Learning for Unsupervised Feature Selection

arXiv:2609.00782v1 Announce Type: new Abstract: Unsupervised feature selection seeks a compact subset of informative features without access to class labels, making feature utility difficult to define

When Metropolis and Hastings Meet Bradley and Terry: Exact MCMC From Preference Voting

arXiv:2609.00905v1 Announce Type: new Abstract: Sampling from distributions conditioned on desired semantic properties is an emerging challenge in modern generative modeling. Metropolis-Hastings (MH)

researcharxiv-cs-lg

When Modality Gap Reduction Fails: Prediction-Level Hubness in CLIP

arXiv:2609.01103v1 Announce Type: new Abstract: Reducing the modality gap between image and text representations in CLIP is widely expected to improve cross-modal alignment and downstream performance.

safetyarxiv-cs-cl

When the Algorithm Becomes the Brand Crisis: A Sociotechnical Theory of Distributed Responsibility and Accountable Transparency

arXiv:2609.00510v1 Announce Type: new Abstract: Artificial intelligence systems increasingly enact market-facing promises through chatbots, recommendation systems, automated decisions, and generative

When Tokenization is Secretly Output Supervision

arXiv:2609.01386v1 Announce Type: new Abstract: Tokenization in language models is treated by default as an input preprocessing decision. We argue that this framing is incomplete: in autoregressive mo

Where Should Experience Live? Hierarchical Hebbian Memory for Continual Vision Transformers

arXiv:2609.00358v1 Announce Type: new Abstract: Vision Transformers provide strong visual representations but typically rely on slowly updated parameters, limiting their ability to organize newly acqu

researcharxiv-cs-cv

Agents

WiseSpec: Requirements-Driven Agents for Code Generation

arXiv:2609.00568v1 Announce Type: cross Abstract: Code generation aims to automatically generate source code from task requirements and has attracted significant attention with the rapid advancement o

agentsarxiv-cs-ai

Hardware

ZimaBlue: Evolving Generalizable World Action Models through Scalable Video Pre-training

arXiv:2609.00188v1 Announce Type: new Abstract: Robotic manipulation faces a fundamental scaling challenge: robust generalization demands broad physical experience, yet action-labeled robot trajectori

hardwarearxiv-cs-cv

A Composition-Aware Pretraining Framework for Geospatial Foundation Models

arXiv:2608.30817v1 Announce Type: cross Abstract: Geospatial foundation models have emerged as state-of-the-art methods for downstream Earth observation tasks. However, existing pretraining methodolog

1 Sept 2026

A Cycle-Consistency Constrained Framework for Dynamic Solution Space Reduction in Noninjective Regression