Search: “evaluation”

Hypencoder Revisited: Reproducibility and Analysis of Non-Linear Scoring for First-Stage Retrieval

arXiv:2604.27037v1 Announce Type: cross Abstract: The Hypencoder, proposed by Killingback et al., is a retrieval framework that replaces the fixed inner-product scoring function used in standard bi-en

researcharxiv-cs-cl

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IACDM: Interactive Adversarial Convergence Development Methodology -- A Structured Framework for AI-Assisted Software Development

DGX agent

arXiv:2604.16399v2 Announce Type: replace-cross Abstract: The widespread adoption of AI-assisted development tools in 2025 -- and the emergence of vibe coding, a practice of generating complete applic

applicationsarxiv-cs-ai

1 May 2026

Imitation Game for Adversarial Disillusion with Chain-of-Thought Reasoning in Generative AI

arXiv:2501.19143v2 Announce Type: replace Abstract: As the cornerstone of artificial intelligence, machine perception confronts a fundamental threat posed by adversarial illusions. These adversarial a

In-context Learning vs. Instruction Tuning: The Case of Small and Multilingual Language Models

arXiv:2503.01611v3 Announce Type: replace Abstract: Instruction following is a critical ability for Large Language Models to perform downstream tasks. The standard approach to instruction tuning has r

safetyarxiv-cs-cl

In-Context Prompting Obsoletes Agent Orchestration for Procedural Tasks

arXiv:2604.27891v1 Announce Type: new Abstract: Agent orchestration frameworks -- LangGraph, CrewAI, Google ADK, OpenAI Agents SDK, and others -- place an external orchestrator above the LLM, tracking

Instruction-Guided Poetry Generation in Arabic and Its Dialects

arXiv:2604.27766v1 Announce Type: cross Abstract: Poetry has long been a central art form for Arabic speakers, serving as a powerful medium of expression and cultural identity. While modern Arabic spe

researcharxiv-cs-ai

InterPartAbility: Text-Guided Part Matching for Interpretable Person Re-Identification

arXiv:2604.27122v1 Announce Type: new Abstract: Text-to-image person re-identification (TI-ReID) relies on natural-language text description to retrieve top matching individuals from a large gallery o

Iterative Definition Refinement for Zero-Shot Classification via LLM-Based Semantic Prototype Optimization

model-releasesarxiv-cs-cv

arXiv:2604.27335v1 Announce Type: new Abstract: Web filtering systems rely on accurate web content classification to block cyber threats, prevent data exfiltration, and ensure compliance. However, cla

JaiTTS: A Thai Voice Cloning Model

arXiv:2604.27607v1 Announce Type: new Abstract: We present JaiTTS-v1.0, a state-of-the-art Thai voice cloning text-to-speech model built through continual training on a large Thai-centric speech corpu

applicationsarxiv-cs-cl

Judge, Then Drive: A Critic-Centric Vision Language Action Framework for Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2604.27366v1 Announce Type: new Abstract: Recent advances in vision language action (VLA) models have shown remarkable potential for autonomous driving by directly mapping multimodal inputs to c

Junk DNA Hypothesis: Pruning Small Pre-Trained Weights Irreversibly and Monotonically Impairs 'Difficult' Downstream Tasks in LLMs

arXiv:2310.02277v4 Announce Type: replace-cross Abstract: We present Junk DNA Hypothesis by adopting a novel task-centric angle for the pre-trained weights of large language models (LLMs). It has been

researcharxiv-cs-ai

Knowledge Graph Representations for LLM-Based Policy Compliance Reasoning

arXiv:2604.27713v1 Announce Type: new Abstract: The risks posed by AI features are increasing as they are rapidly integrated into software applications. In response, regulations and standards for safe

safetyarxiv-cs-ai

Language Ideologies in a Multilingual Society: An LLM-based Analysis of Luxembourgish News Comments

arXiv:2604.27661v1 Announce Type: new Abstract: Detecting language ideologies is a valuable yet complex task for understanding how identities are constructed through discourse. In Luxembourg's multicu

researcharxiv-cs-cl

Latent Adversarial Detection: Adaptive Probing of LLM Activations for Multi-Turn Attack Detection

arXiv:2604.28129v1 Announce Type: cross Abstract: Multi-turn prompt injection follows a known attack path -- trust-building, pivoting, escalation but text-level defenses miss covert attacks where indi

applicationsarxiv-cs-ai

Learning from a single labeled face and a stream of unlabeled data

arXiv:2604.27564v1 Announce Type: new Abstract: Face recognition from a single image per person is a challenging problem because the training sample is extremely small. We consider a variation of this

researcharxiv-cs-lg

Learning Tactile-Aware Quadrupedal Loco-Manipulation Policies

arXiv:2604.27224v1 Announce Type: new Abstract: Quadrupedal loco-manipulation is commonly built on visual perception and proprioception. Yet reliable contact-rich manipulation remains difficult: visio

safetyarxiv-cs-ro

Learning to Aggregate Zero-Shot LLM Agents for Corporate Disclosure Classification

arXiv:2603.20965v2 Announce Type: replace-cross Abstract: This paper studies whether a lightweight supervised aggregator can combine diverse zero-shot large language model outputs into a stronger down

researcharxiv-cs-ai

Learning to Reason: Targeted Knowledge Discovery and Fuzzy Logic Update for Robust Image Recognition

arXiv:2604.27759v1 Announce Type: cross Abstract: Integrating domain knowledge into deep neural networks is a promising way to improve generalization. Existing methods either encode prior knowledge in

applicationsarxiv-cs-ai

Leveraging Verifier-Based Reinforcement Learning in Image Editing

arXiv:2604.27505v1 Announce Type: new Abstract: While Reinforcement Learning from Human Feedback (RLHF) has become a pivotal paradigm for text-to-image generation, its application to image editing rem

Linguistically Informed Multimodal Fusion for Vietnamese Scene-Text Image Captioning: Dataset, Graph Framework, and Phonological Attention

arXiv:2604.27712v1 Announce Type: cross Abstract: Scene-text image captioning requires fusing three information streams -- visual features, OCR-detected text, and linguistic knowledge -- to generate d

safetyarxiv-cs-cl

LLM-based User Profile Management for Recommender System

arXiv:2502.14541v3 Announce Type: replace Abstract: The rapid advancement of Large Language Models (LLMs) has opened new opportunities in recommender systems by enabling zero-shot recommendation witho

applicationsarxiv-cs-cl

LM-CartSeg: Automated Segmentation of Lateral and Medial Cartilage and Subchondral Bone for Radiomics Analysis

arXiv:2512.03449v3 Announce Type: replace Abstract: Background and Objective: Radiomics of knee MRI requires robust, anatomically meaningful regions of interest (ROIs) that jointly capture cartilage a

Low Rank Adaptation for Adversarial Perturbation

model-releasesarxiv-cs-lg

arXiv:2604.27487v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA), which leverages the insight that model updates typically reside in a low-dimensional space, has significantly improved the t

Machine Collective Intelligence for Explainable Scientific Discovery

arXiv:2604.27297v1 Announce Type: new Abstract: Deriving governing equations from empirical observations is a longstanding challenge in science. Although artificial intelligence (AI) has demonstrated

Machine Unlearning for Class Removal through SISA-based Deep Neural Network Architectures

arXiv:2604.27804v1 Announce Type: new Abstract: The rapid proliferation of image generation models and other artificial intelligence (AI) systems has intensified concerns regarding data privacy and us

applicationsarxiv-cs-cv

Making Conformal Predictors Robust in Healthcare Settings: a Case Study on EEG Classification

arXiv:2602.19483v2 Announce Type: replace-cross Abstract: Quantifying uncertainty in clinical predictions is critical for high-stakes diagnosis tasks. Conformal prediction offers a principled approach

applicationsarxiv-cs-ai

Making Logic a First-Class Citizen in Generative ML for Networking

arXiv:2506.23964v3 Announce Type: replace-cross Abstract: Generative ML models are increasingly popular in networking for tasks such as telemetry imputation, prediction, and synthetic trace generation

applicationsarxiv-cs-lg

Hardware

MARS: Efficient, Adaptive Co-Scheduling for Heterogeneous Agentic Systems

arXiv:2604.26963v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as the execution core of autonomous agents rather than as standalone text generators. Agentic w

hardwarearxiv-cs-lg

Measurement Risk in Supervised Financial NLP: Rubric and Metric Sensitivity on JF-ICR

arXiv:2604.27374v1 Announce Type: new Abstract: As LLMs become credible readers of earnings calls, investor-relations Q&A, guidance, and disclosure language, supervised financial NLP benchmarks increa

MIFair: A Mutual-Information Framework for Intersectionality and Multiclass Fairness

arXiv:2604.28030v1 Announce Type: cross Abstract: Fairness in machine learning remains challenging due to its ethical complexity, the absence of a universal definition, and the need for context-specif

safetyarxiv-cs-ai

Models Recall What They Violate: Constraint Adherence in Multi-Turn LLM Ideation

model-releasesarxiv-cs-cl

arXiv:2604.28031v1 Announce Type: new Abstract: When researchers iteratively refine ideas with large language models, do the models preserve fidelity to the original objective? We introduce DriftBench

MultiBLiMP 1.0: A Massively Multilingual Benchmark of Linguistic Minimal Pairs

model-releasesarxiv-cs-cl

arXiv:2504.02768v4 Announce Type: replace Abstract: We introduce MultiBLiMP 1.0, a massively multilingual benchmark of linguistic minimal pairs, covering 101 languages and 2 types of subject-verb agre

Neural Aided Kalman Filtering for UAV State Estimation in Degraded Sensing Environments

arXiv:2604.28107v1 Announce Type: new Abstract: Accurate state estimation of nonlinear dynamical systems is fundamental to modern aerospace operations across air, sea, and space domains. Online tracki

tutorialsarxiv-cs-lg

Noise2Map: End-to-End Diffusion Model for Semantic Segmentation and Change Detection

arXiv:2604.27889v1 Announce Type: new Abstract: Semantic segmentation and change detection are two fundamental challenges in remote sensing, requiring models to capture either spatial semantics or tem

tutorialsarxiv-cs-cv

NORACL: Neurogenesis for Oracle-free Resource-Adaptive Continual Learning

arXiv:2604.27031v1 Announce Type: cross Abstract: In a continual learning setting, we require a model to be plastic enough to learn a new task and stable enough to not disturb previously learned capab

tutorialsarxiv-cs-ai

ObjectGraph: From Document Injection to Knowledge Traversal -- A Native File Format for the Agentic Era

arXiv:2604.27820v1 Announce Type: new Abstract: Every document format in existence was designed for a human reader moving linearly through text. Autonomous LLM agents do not read - they retrieve. This

On the Proper Treatment of Units in Surprisal Theory

arXiv:2604.28147v1 Announce Type: new Abstract: Surprisal theory links human processing effort to the predictability of an upcoming linguistic unit, but empirical work often leaves the notion of a uni

researcharxiv-cs-cl

Optimal Stop-Loss and Take-Profit Parameterization for Autonomous Trading Agent Swarm

arXiv:2604.27150v1 Announce Type: new Abstract: Autonomous crypto trading systems often spend most of their design effort on finding entries, while exits are left to fixed rules that are rarely tested

OptimusKG: Unifying biomedical knowledge in a modern multimodal graph

arXiv:2604.27269v1 Announce Type: new Abstract: Biomedical knowledge graphs (KGs) are widely used in the life sciences, yet many are derived from unstructured documents and therefore lack schema-level

OR-VSKC: Resolving Visual-Semantic Knowledge Conflicts in Operating Rooms with Synthetic Data-Guided Alignment

arXiv:2506.22500v2 Announce Type: replace-cross Abstract: Automated identification of surgical safety risks is critical for improving patient outcomes; however, Multimodal Large Language Models (MLLMs

People-Centred Medical Image Analysis

arXiv:2604.26991v1 Announce Type: cross Abstract: Recent advances in data-centric medical AI have produced highly accurate diagnostic systems, but the emphasis on data curation and performance metrics

Performance-Driven QUBO for Recommender Systems on Quantum Annealers

arXiv:2410.15272v3 Announce Type: replace-cross Abstract: Quantum annealers offer a promising hardware platform for solving combinatorial optimization problems, especially those formulated as Quadrati

safetyarxiv-cs-ai

PhyCo: Learning Controllable Physical Priors for Generative Motion

arXiv:2604.28169v1 Announce Type: cross Abstract: Modern video diffusion models excel at appearance synthesis but still struggle with physical consistency: objects drift, collisions lack realistic reb

PINN-Cast: Exploring the Role of Continuous-Depth NODE in Transformers and Physics Informed Loss as Soft Physical Constraints in Short-term Weather Forecasting

arXiv:2604.27313v1 Announce Type: cross Abstract: Operational weather prediction has long relied on physics-based numerical weather prediction (NWP), whose accuracy comes at the cost of substantial co

Local Ai

Policy-Governed LLM Routing with Intent Matching for Instrument Laboratories

arXiv:2604.26955v1 Announce Type: cross Abstract: AI tutoring systems in engineering labs face a tension between providing sufficient assistance and preserving learning opportunities. Existing systems

local-aiarxiv-cs-ai

Predicting Atomistic Transitions with Transformers

arXiv:2603.06526v2 Announce Type: replace-cross Abstract: Accurate knowledge of the atomistic transition pathways in materials and material surfaces is crucial for many material science problems. Howe

tutorialsarxiv-cs-lg

PVeRA: Probabilistic Vector-Based Random Matrix Adaptation

model-releasesarxiv-cs-cv

arXiv:2512.07703v2 Announce Type: replace Abstract: Large foundation models have emerged in the last years and are pushing performance boundaries for a variety of tasks. Training or even finetuning su

Quantum Masked Autoencoders for Vision Learning

arXiv:2511.17372v2 Announce Type: replace-cross Abstract: Classical autoencoders are widely used to learn features of input data. To improve the feature learning, classical masked autoencoders extend

tutorialsarxiv-cs-ai