Search: “evaluation”

Domain-Specific Hallucination Detection in Large Language Models

arXiv:2609.11878v1 Announce Type: new Abstract: Large language models generate fluent text that can contain unfaithful claims -- a phenomenon known as hallucination. We present a multi-signal detectio

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Research

DR-LabStack: Design and Implementation of a Clinician-Facing Web System for Diabetic Retinopathy Prediction

DGX agent

arXiv:2609.10796v1 Announce Type: new Abstract: Pretrained diabetic retinopathy (DR) prediction models differ in their input fields, serialization formats, preprocessing requirements, and output seman

researcharxiv-cs-lg

11 Sept 2026

Local Ai

EGGROLL, Unrolled: Understanding and Improving Low-Rank Evolution Strategies at Scale

arXiv:2609.10980v1 Announce Type: new Abstract: EGGROLL makes evolution strategies (ES) practical for LLMs by replacing dense Gaussian weight perturbations with low-rank Gaussian products, often of ra

local-aiarxiv-cs-lg

Agents

Emergent Risks in Generative Multi-Agent Systems

arXiv:2603.27771v3 Announce Type: replace-cross Abstract: Multi-agent systems composed of large generative models are rapidly moving from laboratory prototypes to real-world deployments, where they jo

agentsarxiv-cs-cl

Enabling Knowledge Graph Understanding at Scale with the EXplore Your Graphs ENgine (EXYGEN)

arXiv:2609.11569v1 Announce Type: cross Abstract: We present EXYGEN (EXplore Your Graphs ENgine), a framework for knowledge graph (KG) understanding that enables conversational access to KGs at scale.

Estimating Inconsistency Response Surfaces under Uncertainty in Cyber-Physical System Development

arXiv:2609.11331v1 Announce Type: new Abstract: Cyber-Physical Systems (CPS) are commonly represented through multiple interconnected models. During development, CPS consistency requires that shared m

Explainability Assistant: A Conversational XAI Interface for Interpreting Energy Consumption Models

arXiv:2609.11860v1 Announce Type: cross Abstract: Energy consumption forecasting relies on increasingly complex machine learning (ML) models, such as Genetic Programming-based symbolic regressors, who

Geospatial Foundation Models Capture Health-Relevant Dimensions of Place Beyond Conventional Social Risk Indices

arXiv:2609.11689v1 Announce Type: cross Abstract: Area-based social risk indices summarize residents' socioeconomic conditions but incompletely capture physical features of place that may affect healt

Hologram Representation via Quadratic Phase Gaussian Splatting

arXiv:2609.11434v1 Announce Type: cross Abstract: We introduce Complex-Valued Quadratic Phase Gaussian (CVQPG), a novel hologram representation method that replaces standard 2D Gaussian representation

Improving 5G AI-RAN MCS Selection by Predicting Retransmissions

arXiv:2609.09324v1 Announce Type: cross Abstract: Link Adaptation (LA) in 5G NR is inherently reactive, relying on channel measurements and HARQ feedback that may become quickly obsolete when the chan

Leveraging LLMs for Context-Aware Implicit Textual and Multimodal Hate Speech Detection

arXiv:2510.15685v2 Announce Type: replace Abstract: This paper investigates the use of an LLM to generate auxiliary background context for social media posts, and explores four methods to incorporate

LLM-Anchored Paralinguistic Enrichment for Alzheimer's Disease Detection

arXiv:2609.10896v1 Announce Type: new Abstract: Speech-based automatic detection of Alzheimer's disease (AD) provides a non-invasive and scalable approach to early cognitive screening. AD affects both

MC-DeTra: Motion-Consistent Joint Object Detection and Socially-Aware Trajectory Forecasting in Bird's-Eye-View Images

arXiv:2609.11717v1 Announce Type: new Abstract: Unified models for object detection and trajectory forecasting aim to merge perception and prediction for autonomous driving, refining actor trajectorie

Measuring Progress in Reasoning Toward Mathematical Discovery with Automatic Verification

arXiv:2603.15617v2 Announce Type: replace Abstract: Can AI make progress on important, unsolved mathematical problems? Large language models are now capable of sophisticated mathematical and scientifi

MindTopo: Can Foundation Models Reason in Topological Space?

arXiv:2609.11900v1 Announce Type: cross Abstract: Spatial reasoning depends not only on metric properties such as distance, angle, and shape, but also on topological relations that remain invariant un

MisEdu-RAG: A Misconception-Aware Dual-Hypergraph RAG for Novice Math Teachers

arXiv:2604.04036v2 Announce Type: replace-cross Abstract: Novice math teachers often encounter students' mistakes that are difficult to diagnose and remediate. Misconceptions are especially challengin

Multimodal Taxonomic Conditioning for Generative Plankton Imagery

arXiv:2609.11673v1 Announce Type: new Abstract: Automated plankton imaging produces severely long-tailed datasets, where the rare taxa of greatest ecological interest have too few images to train or e

On the Impact of Anonymization on the Performance of Large Language Models

arXiv:2609.11335v1 Announce Type: new Abstract: As large language models are increasingly deployed in sensitive domains, anonymizing input data to protect personally identifiable information has becom

Optimizing AI Inference Across the Deployment Stack

arXiv:2609.10550v1 Announce Type: cross Abstract: AI deployment performance is shaped not by model architecture alone, but by interactions among compression, compiler transformations, and serving poli

Pairit: A Platform for Live Experiments on Human-AI Collaboration

arXiv:2609.09789v1 Announce Type: cross Abstract: Organizational design in the era of artificial intelligence requires experimental methods that can test how human-AI groups coordinate, delegate, and

researcharxiv-cs-ai

Predicting Privacy Leakage from Weight Spectral Density

arXiv:2609.11780v1 Announce Type: new Abstract: Membership inference attacks (MIAs) are widely used to audit the privacy disclosure risk of machine learning models, however current state-of-the-art at

Quantifying Logical Consistency in Transformers via Query-Key Alignment

arXiv:2502.17017v1 Announce Type: cross Abstract: Large language models (LLMs) have demonstrated impressive performance in various natural language processing tasks, yet their ability to perform multi

safetyarxiv-cs-ai

Reference-Based Bias Detection in LLMs via Relative Representations of Hidden States

arXiv:2609.10060v1 Announce Type: new Abstract: Existing bias auditing methods typically rely on model outputs, requiring costly benchmarks or judge models and potentially missing internal shifts that

Hardware

Reification as a Transferable Vocabulary: Zero-Shot Link Prediction with Vanilla GNNs

arXiv:2609.11347v1 Announce Type: new Abstract: Knowledge graph foundation models such as ULTRA achieve zero-shot link prediction on unseen graphs through dedicated architectures that hard-code a tran

hardwarearxiv-cs-lg

Tutorials

Rethinking Handwritten Character Recognition

arXiv:2609.10572v1 Announce Type: new Abstract: Non-Latin handwritten character recognition (HCR) remains understudied. Dominant methods consider it as generic image classification, which uses model s

tutorialsarxiv-cs-cv

SegCol Challenge: Semantic Segmentation for Tools and Fold Edges in Colonoscopy data

arXiv:2412.16078v2 Announce Type: replace Abstract: Improving the reliability and completeness of colonoscopic inspection is critical for reducing missed lesions and improving colorectal cancer preven

SIRF: A Spec-Internalized Risk Foundation Model for Industrial Content Risk Control

arXiv:2609.11752v1 Announce Type: cross Abstract: For industrial content risk control, the real deployment constraint is not average accuracy but how much risk can be auto-handled under high precision

safetyarxiv-cs-cl

Solving Few-Shot Multiobjective Multitask Optimization via Iterative Sequential Transfer

arXiv:2609.11228v1 Announce Type: new Abstract: Applying knowledge transfer across multiple optimization tasks, multitask optimization (MTO) emerges as a promising approach to solving synergistic opti

Spec-Harness: Measuring and Improving Behavioral Adequacy of LLM-Synthesized Formal Specifications

arXiv:2604.00280v2 Announce Type: replace-cross Abstract: Formal specifications play a central role in ensuring software reliability, yet automatically synthesizing high-quality specifications remains

Strategic Type Spaces

arXiv:2606.08297v2 Announce Type: replace-cross Abstract: We provide a strategic foundation for information: in any given game with incomplete information we define strategic quotients as information

Agents

TrajFusionNet+: Transformer-Based Prediction of Pedestrian Crossing Intention via Fusion of Trajectory Representations and Scene Graphs

arXiv:2609.10806v1 Announce Type: new Abstract: The pedestrian crossing intention task involves predicting whether pedestrians are likely to cross the road from the point of view of an autonomous vehi

agentsarxiv-cs-cv

Watermarks Without Verification: AI Text Watermarking After the EU AI Act

arXiv:2609.09604v1 Announce Type: cross Abstract: On August 2, 2026, the obligations of Article 50 of the EU AI Act took effect, requiring generative AI providers to mark the content their systems pro

What Language is This? Ask Your Tokenizer

arXiv:2602.17655v3 Announce Type: replace Abstract: Language Identification (LID) is an important component of many multilingual natural language processing pipelines, where it facilitates corpus cura

Whisper-Based Speech Transcription from Videos Across Multiple Languages for Cross-Cultural Understanding

arXiv:2609.11772v1 Announce Type: cross Abstract: Cross-cultural understanding has become increasingly important in today's highly connected, cross-national world. The success of LLM-based technologie

3rd Place Solution to Human Motion Challenges in Real-World and Clinical Settings (MoCha) @ECCV2026: Language-Aligned Motion Representations for Domain-Generalizable UPDRS-Gait Severity Estimation

arXiv:2609.10187v1 Announce Type: new Abstract: In this work, we introduce language-aligned motion representations for domain-generalizable UPDRS-Gait severity estimation, aiming to learn semantically

A Block Tensor Train Burer-Monteiro Framework for Low-Rank Quantum State Tomography

arXiv:2609.09457v1 Announce Type: cross Abstract: Quantum state tomography is a fundamental technique for estimating the state of a quantum system from measured data and plays a crucial role in evalua

Applications

A Kernel-Based Modular Discriminant Analysis Framework for Small-Sample Learning

arXiv:2609.09910v1 Announce Type: new Abstract: The small-sample-size (SSS) problem remains a fundamental challenge in machine learning when labeled data are scarce due to cost, accessibility, or ethi

applicationsarxiv-cs-lg

A statistical approach to bias in zero-shot learning: the lens of handwriting recognition

arXiv:2609.10084v1 Announce Type: cross Abstract: Generalized zero-shot learning (GZSL) has emerged as an important paradigm for visual recognition systems that must generalize to classes that were no

safetyarxiv-cs-cv

Active Adaptation, Not Static Defense: Temporal Dynamics of Preventative Steering in Adversarial Fine-Tuning

arXiv:2609.10142v1 Announce Type: new Abstract: Large language models remain fragile against malicious fine-tuning, motivating training-time defenses against harmful persona drift. Preventative Steeri

AgentFairBench: Do LLM Agents Discriminate When They Act?

arXiv:2606.16723v2 Announce Type: replace Abstract: Large language model (LLM) agents increasingly take actions (screening applicants, recommending credit, triaging patients), yet fairness for LLMs is

Agentic ML Exploration (A-MLE) for Ads Ranking

arXiv:2609.08248v1 Announce Type: new Abstract: Modern industrial ads ranking stacks are increasingly bottlenecked not by model capacity or training compute, but by the throughput of human ML iteratio

Albedo Estimation via Latent Bridge Matching

arXiv:2609.09884v1 Announce Type: new Abstract: Recent advances in Intrinsic Image Decomposition (IID) have increasingly relied on generative models. However, progress remains limited by three key cha

An Auditable Symbolic-RAG-Generative AI Architecture for Goal-Oriented Conversation Orchestration

arXiv:2609.07152v1 Announce Type: new Abstract: Goal-oriented conversational systems must answer factual questions, understand visitor-provided information, and advance business objectives without bec

safetyarxiv-cs-ai

Agents

An emancipatory vision for designing (generative) AI for learner flourishing

arXiv:2609.07715v1 Announce Type: cross Abstract: The hype around generative AI seems to promise unprecedented productivity (and learning) gains. However, these technologies' increasing agentic featur

agentsarxiv-cs-ai

An Evolutionary Framework for Automatic Optimization Benchmark Generation via Large Language Models

arXiv:2601.12723v3 Announce Type: replace-cross Abstract: Optimization benchmarks play a fundamental role in assessing algorithm performance; however, existing artificial benchmarks often fail to capt

AstroSpecLM: A Spectrum-Language Model for Evidence-Grounded Astronomical Spectral Analysis

arXiv:2609.07102v1 Announce Type: cross Abstract: Astronomical spectra encode rich physical information, but drawing scientific conclusions from spectral features typically requires expert interpretat

researcharxiv-cs-ai

AttnCompress: Dynamic Attention-Guided Trajectory Compression for Software Engineering Agents

arXiv:2609.08318v1 Announce Type: cross Abstract: The transition from human-centric assistance to Autonomous Software Engineering (ASE) agents has enabled the resolution of complex real-world SE tasks

Audio-Maestro: Enhancing Large Audio-Language Models with Tool-Augmented Reasoning

arXiv:2510.11454v2 Announce Type: replace-cross Abstract: Recent advancements in large multimodal models (LMMs) have shown strong capabilities in audio understanding. However, most systems rely solely