Search: “evaluation”

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

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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

2 Sept 2026

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

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

researcharxiv-cs-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

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

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

model-releasesarxiv-cs-cv

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)

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.

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

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

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

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

arXiv:2507.04659v3 Announce Type: replace Abstract: To address the challenges posed by the heavy reliance of multi-output models on preset probability distributions and embedded prior knowledge in non

A Degradation-Tolerance Benchmark for Camera-Only End-to-End Driving

model-releasesarxiv-cs-ro

arXiv:2608.29005v1 Announce Type: new Abstract: Camera-only end-to-end (E2E) driving models are nearing deployment, where the camera stream is degraded by blur, noise, low light, weather, frame loss,

A Mental Model Based Framework of Trust

arXiv:2301.12569v2 Announce Type: replace Abstract: Handling trust is a core requirement of effective interaction between people and AI agents. Thus, any decision-making framework designed to work wit

A rigor-matched audit of periodic-step layer skipping for efficient llm inference: conflayers versus swift, with a supplemental analysis of trained routing alternatives

arXiv:2608.28846v1 Announce Type: cross Abstract: Layer-skipping methods for efficient LLM inference decide, at some granularity, which transformer layers to execute for a given input. We present a ri

researcharxiv-cs-ai

A Target-Centric Survey of Quantization-Aware Training

arXiv:2608.29667v1 Announce Type: new Abstract: The rapid development of LLMs incurs prohibitive memory footprints and intensive computational demands. Quantization-Aware Training (QAT) techniques hav

A Universal Context-Reuse Layer for Cross-Model KV Sharing

arXiv:2608.30963v1 Announce Type: cross Abstract: Modern large language model (LLM) serving systems increasingly operate over repeated or shared context, yet each model typically performs its own pref

A^2Agent: Action-Aware Reinforcement Learning for Repository-Level Code Localization Agents

arXiv:2608.29831v1 Announce Type: new Abstract: Localizing issue-relevant code regions is a critical step in automated software engineering. However, due to their reliance on sparse trajectory-level s

local-aiarxiv-cs-cl

'Act Like a 5th Grader' is Not Enough: Bounding Knowledge in LLM-Based User Simulators

arXiv:2608.30033v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to simulate human behavior but frequently fail to exhibit realistic cognitive constraints, sufferin

ACTD: Anchor-Based Cross-Tokenizer Distillation with Residual Regularization

arXiv:2608.29662v1 Announce Type: new Abstract: Knowledge distillation effectively transfers reasoning capabilities from large language models to lightweight student models. To enable knowledge transf

ActiveAugment: Online Active Learning for Augmentation Selection in Deep Learning

arXiv:2608.28923v1 Announce Type: cross Abstract: Data augmentation is a cornerstone of deep learning pipelines, yet existing strategies treat it as a static, model-agnostic preprocessing step, either

AdaVLA: Adaptive Step Flow Matching for Training-free Acceleration of Vision-Language-Action Models

model-releasesarxiv-cs-lg

arXiv:2608.29208v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models, built upon Vision-Language Models (VLMs), have significantly enhanced robotic capabilities by leveraging internet

Adversarial Calibration Attack on Autonomous Vehicles

model-releasesarxiv-cs-cv

arXiv:2608.28778v1 Announce Type: cross Abstract: Autonomous vehicles (AVs) rely on accurate camera-LiDAR calibration for multimodal sensor fusion. In practice, calibration can drift due to vibration,

Adversarial Online Classification with a Preview

arXiv:2608.29503v1 Announce Type: new Abstract: Worst-case online classification is governed by sequential complexity, such as Littlestone dimension, and can be impossible even for statistically simpl

AIA^{2}: Attribute-Agnostic Imbalance Augmentation for Subgroup Robustness

arXiv:2608.30297v1 Announce Type: new Abstract: Attributes describing data content and context can induce diverse imbalance patterns that go beyond label imbalance alone. However, existing studies pri

ALTSTEER: Selective Safety Steering for Moving Beyond Hard Refusals to Constructive Alternatives

model-releasesarxiv-cs-cl

arXiv:2608.30197v1 Announce Type: new Abstract: Safety alignment is essential for deploying large language models, requiring systems to prevent harmful compliance while preserving helpfulness on benig

An evidence-guided reinforcement learning method to improve psychiatric reasoning in small language models

arXiv:2602.06449v2 Announce Type: replace Abstract: Privacy and computational constraints limit the use of large language models in psychiatry, while adapting small language models (SLMs) often requir

An Open-Source, Event-Driven Pipeline for Cryptocurrency Market Data: Ingestion, Forecasting, and On-Chain Fraud Detection

arXiv:2608.29973v1 Announce Type: new Abstract: Cryptocurrency markets generate high-frequency, multi-source data that is expensive to work with unless a team already has commercial-grade streaming an

Anchoring Speech with Semantics: A Multimodal Adapter Mechanism for Automatic Speech Recognition in Low-Resource Languages

arXiv:2608.29239v1 Announce Type: new Abstract: Low-resource ASR remains difficult because scarce transcripts provide limited supervised evidence for target-side generation. To address this gap, we pr

AnnotateAnything: Automatic Annotation of 3D Assets for Robot Manipulation

model-releasesarxiv-cs-cv

arXiv:2606.17446v2 Announce Type: replace-cross Abstract: Simulation enables scalable robot data collection, but raw 3D assets provide only geometry, lacking the semantic, interactive, and physical kn

Annotated Surrogate Retrieval for Polish Statutory Law

model-releasesarxiv-cs-cl

arXiv:2608.30929v1 Announce Type: new Abstract: We present a family of retrieval methods for Polish statutory law built on document surrogates: language-model annotations attached to statutory article

APPSolver: Adaptive Patch Partitioning for Point-Wise Ship Flow Prediction on Unstructured Meshes

arXiv:2608.29355v1 Announce Type: new Abstract: Large non-uniform point sets make direct attention-based surrogate modeling costly for ship hydrodynamics. We introduce APPSolver, a point-wise flow-pre

researcharxiv-cs-ai

Arabic Safety Alignment as Selective Refusal: An Empirical Study of SFT, DPO, and Guard Calibration

arXiv:2608.29378v1 Announce Type: cross Abstract: Arabic large language models must refuse harmful prompts without over-refusing benign or sensitive prompts, yet a single refusal rate hides this trade

Tutorials

ARMOR: Manifold-Oriented Training for Adversarially Robust Aerial Object Detection under Data Scarcity

arXiv:2608.29510v1 Announce Type: new Abstract: Aerial object detection is increasingly deployed in real-world applications, but models remain vulnerable to physical, universal adversarial patches tha

tutorialsarxiv-cs-cv

ASTRA - Agentic System for Ticket Resolution and Analysis

arXiv:2608.28790v1 Announce Type: cross Abstract: Technical operations teams resolve large volumes of incidents by synthesizing fragmented evidence from ticket text, historical cases, system logs, and

AtlasNLP: A Country-Aware Atlas of Dataset Representation in NLP

arXiv:2608.30107v1 Announce Type: cross Abstract: Understanding which countries are represented in NLP datasets is essential for identifying gaps, targeting data collection, measuring progress, and in

Attribute-Based Activation Steering of LLMs for Group-Specific Explanation Generation

arXiv:2608.29215v1 Announce Type: new Abstract: To effectively enable people to understand new topics, explanations should be tailored to their backgrounds and abilities. So far, prompting alone has b

Augmenting Interviewer Judgments of Patient Experience with Automatic Language Analysis

arXiv:2608.31007v1 Announce Type: cross Abstract: Understanding how psychiatric patients subjectively experienced a clinical conversation is important for feedback and alliance-related process monitor

Autoencoders in Function Space

arXiv:2408.01362v4 Announce Type: replace-cross Abstract: Autoencoders have found widespread application in both their original deterministic form and in their variational formulation (VAEs). In scien

Automated pipeline for herbarium label digitization

arXiv:2608.28676v1 Announce Type: new Abstract: Digitized herbarium collections, now comprising over 100 million freely accessible specimen images, have become a critical resource for addressing funda

local-aiarxiv-cs-cv