Search: “evaluation”

TCMIIES: A Browser-Based LLM-Powered Intelligent Information Extraction System for Academic Literature

arXiv:2605.07507v1 Announce Type: new Abstract: The exponential growth of academic publications has created an urgent need for automated tools capable of extracting structured knowledge from unstructu

local-aiarxiv-cs-cl

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Model Releases

TEA-Bench: A Systematic Benchmarking of Tool-enhanced Emotional Support Dialogue Agent

DGX agent

arXiv:2601.18700v2 Announce Type: replace Abstract: Emotional Support Conversation requires not only affective expression but also grounded instrumental support to provide trustworthy guidance. Howeve

model-releasesarxiv-cs-ai

11 May 2026

The Coupling Tax: How Shared Token Budgets Undermine Visible Chain-of-Thought Under Fixed Output Limits

arXiv:2605.07686v1 Announce Type: new Abstract: Chain-of-thought reasoning is often treated as a monotone way to improve language-model accuracy by letting a model think longer. We identify a counterv

The Moltbook Files: A Harmless Slopocalypse or Humanity's Last Experiment

arXiv:2605.07462v1 Announce Type: cross Abstract: Moltbook is a Reddit-like platform where OpenClaw agents post, comment, and vote at scale - a so far unprecedented incident that comes with serious sa

The Position Curse: LLMs Struggle to Locate the Last Few Items in a List

model-releasesarxiv-cs-cl

arXiv:2605.07127v1 Announce Type: cross Abstract: Modern large language models (LLMs) can find a needle in a haystack (locating a single relevant fact buried among hundreds of thousands of irrelevant

Think Before You Drive: World Model-Inspired Multimodal Grounding for Autonomous Vehicles

arXiv:2512.03454v4 Announce Type: replace-cross Abstract: Interpreting natural-language commands to localize target objects is critical for autonomous driving (AD). Existing visual grounding (VG) meth

local-aiarxiv-cs-ai

Three-in-One World Model: Energy-Based Consistency, Prediction, and Counterfactual Inference for Marketing Intervention

arXiv:2605.07199v1 Announce Type: new Abstract: Marketing decisions reflect the interaction of latent consumer heterogeneity, time-varying internal states, and explicit interventions, a structure that

Agents

Towards Autonomous Business Intelligence via Data-to-Insight Discovery Agent

arXiv:2605.07202v1 Announce Type: new Abstract: Transforming fragmented enterprise data into actionable insights remains a significant challenge for LLMs, constrained by complex database schemas, limi

agentsarxiv-cs-ai

Hardware

Towards Billion-scale Multi-modal Biometric Search

arXiv:2605.07655v1 Announce Type: cross Abstract: Searching a multi-biometric database of a billion records for a country-level identity system requires pushing the limits of all aspects of a biometri

hardwarearxiv-cs-ai

Towards Closing the Autoregressive Gap in Language Modeling via Entropy-Gated Continuous Bitstream Diffusion

model-releasesarxiv-cs-cl

arXiv:2605.07013v1 Announce Type: new Abstract: Diffusion language models (DLMs) promise parallel, order-agnostic generation, but on standard benchmarks they have historically lagged behind autoregres

Towards Fairness under Label Bias in Image Segmentation: Impact, Measurement and Mitigation

arXiv:2605.06891v1 Announce Type: new Abstract: Labeled datasets reflect the biases of their annotation pipelines, which sometimes introduce label bias: group-conditional label errors that cause syste

safetyarxiv-cs-cv

Agents

Towards Security-Auditable LLM Agents: A Unified Graph Representation

arXiv:2605.06812v1 Announce Type: new Abstract: LLM-based agentic systems are rapidly evolving to perform complex autonomous tasks through dynamic tool invocation, stateful memory management, and mult

agentsarxiv-cs-ai

Tracing Uncertainty in Language Model 'Reasoning'

model-releasesarxiv-cs-ai

arXiv:2605.07776v1 Announce Type: cross Abstract: Language model (LM) 'reasoning', commonly described as Chain-of-Thought or test-time scaling, often improves benchmark performance, but the dynamics u

Training-Free Multimodal Large Language Model Orchestration

arXiv:2508.10016v3 Announce Type: replace Abstract: Building interactive omni-modal assistants often relies on end-to-end multimodal alignment to fuse heterogeneous modalities, which incurs substantia

safetyarxiv-cs-cl

TRAJGANR: Trajectory-Centric Urban Multimodal Learning via Geospatially Aligned Neural Representations

arXiv:2605.06990v1 Announce Type: new Abstract: Multimodal self-supervised learning (MSSL) has emerged as a key paradigm for pretraining geospatial foundation models. However, existing geospatial MSSL

safetyarxiv-cs-cv

Transformer-Based Wildlife Species Classification from Daily Movement Trajectories

arXiv:2605.06726v1 Announce Type: new Abstract: Inferring the identity of wildlife species from daily movement data alone is a challenging task. We train sequence models on large-scale, 7-species GPS

researcharxiv-cs-lg

TRAS: An Interactive Software for Tracing Tree Ring Cross Sections

arXiv:2605.08025v1 Announce Type: new Abstract: Tree ring marking remains a key step in dendrometry and dendrochronology, but it is often performed manually, making the process time-consuming, subject

researcharxiv-cs-cv

Tyche: One Step Flow for Efficient Probabilistic Weather Forecasting

arXiv:2605.06916v1 Announce Type: new Abstract: Probabilistic weather forecasting requires not only accurate trajectories, but calibrated distributions over plausible atmospheric futures. Recent data-

researcharxiv-cs-lg

Tutorials

Uncovering Hidden Systematics in Neural Network Models for High Energy Physics

arXiv:2605.07470v1 Announce Type: new Abstract: Neural networks (NNs) are inherently multidimensional classifiers that learn complex, non-linear relationships among input observables. While their flex

tutorialsarxiv-cs-lg

UniD-Shift: Towards Unified Semantic Segmentation via Interpretable Share-Private Multimodal Decomposition

arXiv:2605.07356v1 Announce Type: new Abstract: Semantic segmentation of large-scale 3D point clouds is crucial for applications such as autonomous driving and urban digital twins. However, the sparse

safetyarxiv-cs-cv

Tutorials

UniV2D: Bridging Visual Restoration and Semantic Perception for Underwater Salient Object Detection

arXiv:2605.07146v1 Announce Type: new Abstract: Underwater salient object detection (USOD) plays a vital role in marine vision tasks but remains fundamentally challenging due to severe visual degradat

tutorialsarxiv-cs-cv

User eXperience Perception Insights Dataset (UXPID): Synthetic User Feedback from Public Industrial Forums

arXiv:2509.11777v2 Announce Type: replace Abstract: Customer feedback in industrial forums offers rich but underexplored insights into real-world product experience. Yet systematic analysis remains ch

applicationsarxiv-cs-cl

Vaporizer: Breaking Watermarking Schemes for Large Language Model Outputs

arXiv:2605.07481v1 Announce Type: cross Abstract: In this paper, we investigate the recent state-of-the-art schemes for watermarking large language models (LLMs) outputs. These techniques are claimed

applicationsarxiv-cs-ai

Vibe coding before the trend

arXiv:2605.07751v1 Announce Type: cross Abstract: Early 2025 we ran a series of vibe coding challenges across four different student cohorts. The cohorts included 54 ICT students, 24 digital marketing

applicationsarxiv-cs-ai

WeatherSyn: An Instruction Tuning MLLM For Weather Forecasting Report Generation

arXiv:2605.07522v1 Announce Type: new Abstract: Accurate weather forecast reporting enables individuals and communities to better plan daily activities and agricultural operations. However, the curren

researcharxiv-cs-cl

When Descent Is Too Stable: Event-Triggered Hamiltonian Learning to Optimize

arXiv:2605.06868v1 Announce Type: new Abstract: Fixed-budget nonconvex optimization can fail not because local descent is unstable, but because it is too stable: after reaching a nearby stationary poi

safetyarxiv-cs-lg

When Losses Align: Gradient-Based Composite Loss Weighting for Efficient Pretraining

arXiv:2605.07756v1 Announce Type: cross Abstract: Modern deep models are often pretrained on large-scale data with missing labels using composite objectives, where the relative weights of multiple los

Where to Spend Rollouts: Hit-Utility Optimal Rollout Allocation for Group-Based RLVR

arXiv:2605.07114v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has emerged as a central paradigm for improving the reasoning capabilities of large language model

Why do Large Language Models Fail in Low-resource Translation? Unraveling the Token Dynamics of Large Language Models for Machine Translation

arXiv:2605.07533v1 Announce Type: new Abstract: Large Language Models (LLMs) have recently demonstrated strong performance in machine translation (MT). However, most prior work focuses on improving or

researcharxiv-cs-cl

3D Ultrasound-Derived Pseudo-CT Synthesis Using a Transformer-Augmented Residual Network for Real-Time Operator Guidance

arXiv:2605.04856v1 Announce Type: new Abstract: Computed tomography (CT) is indispensable for clinical diagnosis and image-guided interventions but exposes patients to ionizing radiation, motivating t

local-aiarxiv-cs-cv

A Bayesian Approach for Task-Specific Next-Best-View Selection with Uncertain Geometry

arXiv:2605.05095v1 Announce Type: cross Abstract: We develop a framework for task-specific active next-best-view selection in 3D reconstruction from point clouds, by casting the problem in the languag

researcharxiv-cs-cv

A Consistency-Centric Approach to Set-Based Optimization with Multiple Models of Unranked Fidelity

arXiv:2605.04051v1 Announce Type: cross Abstract: In complex real-world settings, optimization is challenged by the presence of diverse models of differing fidelity. In many optimization problems, a s

applicationsarxiv-cs-lg

A Fast Model Counting Algorithm for Two-Variable Logic with Counting and Modulo Counting Quantifiers

arXiv:2605.03391v1 Announce Type: cross Abstract: Weighted first-order model counting (WFOMC) is a central task in lifted probabilistic inference: It asks for the weighted sum of all models of a first

A Foundation Model for Zero-Shot Logical Rule Induction

arXiv:2605.04916v1 Announce Type: cross Abstract: Inductive Logic Programming (ILP) learns interpretable logical rules from data. Existing methods are transductive: their learned parameters are bound

applicationsarxiv-cs-lg

A Hybrid Method for Low-Resource Named Entity Recognition

arXiv:2605.04489v1 Announce Type: cross Abstract: Named Entity Recognition (NER) is a critical component of Natural Language Processing with diverse applications in information extraction and conversa

applicationsarxiv-cs-cl

Tutorials

A Hybrid Quantum-Classical Framework for Financial Volatility Forecasting Based on Quantum Circuit Born Machines

arXiv:2603.09789v2 Announce Type: replace Abstract: Accurate financial volatility forecasting is crucial but challenged by the non-linear, highly correlated nature of market data. Recently, quantum co

tutorialsarxiv-cs-lg

Hardware

A Physics-Aware Framework for Short-Term GPU Power Forecasting of AI Data Centers

arXiv:2605.04074v1 Announce Type: new Abstract: AI data centers experience rapid fluctuations in power demand due to the heterogeneity of computational tasks that they have to support. For example, th

hardwarearxiv-cs-lg

A Scalable Multi-Task Model for Virtual Sensors

arXiv:2601.20634v2 Announce Type: replace Abstract: Virtual sensors replace expensive physical sensors in critical applications through machine learning by predicting target signals from available mea

A Skill-Based AI Agentic Pipeline for Library of Congress Subject Indexing

arXiv:2605.03537v1 Announce Type: cross Abstract: This paper presents a modular AI agentic skill pipeline for automating subject indexing with Library of Congress Subject Headings (LCSH). Subject inde

A Universal Space of Brain Dynamics for Unveiling Cognitive Transitions and Individual Differences

arXiv:2605.02936v1 Announce Type: cross Abstract: Representing dynamical systems through data-driven universal spaces has proven effective; however, achieving this universality for human brain activit

AdapShot: Adaptive Many-Shot In-Context Learning with Semantic-Aware KV Cache Reuse

arXiv:2605.03644v1 Announce Type: new Abstract: Many-Shot In-Context Learning (ICL) has emerged as a promising paradigm, leveraging extensive examples to unlock the reasoning potential of Large Langua

Adapting Large Language Models to a Low-Resource Agglutinative Language: A Comparative Study of LoRA and QLoRA for Bashkir

model-releasesarxiv-cs-cl

arXiv:2605.04948v1 Announce Type: new Abstract: This paper presents a comparative study of parameter-efficient fine-tuning (PEFT) methods, including LoRA and QLoRA, applied to the task of adapting lar

Adaptive Consensus in LLM Ensembles via Sequential Evidence Accumulation: Automatic Budget Identification and Calibrated Commit Signals

arXiv:2605.04236v1 Announce Type: new Abstract: Large Language Model ensembles improve reasoning accuracy up to a performance boundary; beyond it, additional deliberation degrades accuracy. Static-bud

researcharxiv-cs-lg

Adaptive Dual-Path Framework for Covert Semantic Communication

arXiv:2605.03423v1 Announce Type: new Abstract: This paper proposes a novel adaptive dual-path framework for covert semantic communication (SemCom), which integrates covert information transmission wi

Adaptive Ensemble Aggregation for Actor-Critics

arXiv:2507.23501v2 Announce Type: replace Abstract: Ensembles are ubiquitous in off-policy actor-critic learning, yet their efficacy depends critically on how they are aggregated. Current methods typi

Adaptive Learning Strategies for AoA-Based Outdoor Localization: A Comprehensive Framework

arXiv:2605.05055v1 Announce Type: new Abstract: Localization in 5G and 6G networks is essential for important use cases such as intelligent transportation, smart factories, and smart cities. Although

local-aiarxiv-cs-lg

Aes3D: Aesthetic Assessment in 3D Gaussian Splatting

model-releasesarxiv-cs-cv

arXiv:2605.05155v1 Announce Type: new Abstract: As 3D Gaussian Splatting (3DGS) gains attention in immersive media and digital content creation, assessing the aesthetics of 3D scenes becomes important

Agent-Based Modeling of Low-Emission Fertilizer Adoption for Dairy Farm Decarbonisation using Empirical Farm Data

arXiv:2605.03648v1 Announce Type: new Abstract: To understand complex system dynamics in dairy farming, it is essential to use modeling tools that capture farm heterogeneity, social interactions, and