Search: “evaluation”

CPAgents: Agentic Composite Phenotype Generation for Cardiac Disease Association

arXiv:2606.28179v1 Announce Type: cross Abstract: Identifying robust associations between cardiac imaging phenotypes and clinical diseases is fundamental to population-scale cardiovascular research an

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

Curriculum-guided Change Detection Training: Toward Accurate Serac Fall Monitoring

DGX agent

arXiv:2606.28012v1 Announce Type: new Abstract: Change Detection (CD) aims to identify semantic or structural changes from nearly registered multi-temporal images. While recent advances in training me

model-releasesarxiv-cs-cv

29 Jun 2026

Deployment-Side Adaptiveness in Multi-Horizon Volatility Forecasting

arXiv:2606.27688v1 Announce Type: cross Abstract: In financial forecasting, predictive performance depends not only on which model is trained, but also on how the trained model is deployed. We study t

DMind Benchmark: Toward a Holistic Assessment of LLM Capabilities across the Web3 Domain

arXiv:2504.16116v4 Announce Type: replace-cross Abstract: The Web3 ecosystem, underpinned by cryptographic primitives and decentralized consensus, represents a high-stakes environment where software v

From Signals to Transfer: A Factorised Study of Probe-Based Uncertainty Estimation in Large Language Models

arXiv:2606.27679v1 Announce Type: cross Abstract: Probe-based uncertainty estimation (UE) has emerged as a prominent approach to detect hallucinations in Large Language Models (LLMs) by learning uncer

HAT-4D: Lifting Monocular Video for 4D Multi-Object Interactions via Human-Agent Collaboration

arXiv:2606.28215v1 Announce Type: cross Abstract: Extracting dynamic 4D object interactions from massive, in-the-wild monocular videos offers a highly efficient data collection pathway for scaling Emb

HumanMoveVQA: Can Video MLLMs reason about human movement in videos?

arXiv:2606.27999v1 Announce Type: new Abstract: Despite the rapid advance of Multimodal Large Language Models (MLLMs) in high-level video understanding, a fundamental bottleneck remains: these models

Internalizing the Future: A Unified Agentic Training Paradigm for World Model Planning

arXiv:2606.27483v1 Announce Type: new Abstract: Large language model (LLM) agents have demonstrated strong capability in sequential decision-making, yet they remains fundamentally reactive in long-hor

Tutorials

Latent Visual Diffusion Reasoning with Monte Carlo Tree Search

arXiv:2606.27988v1 Announce Type: new Abstract: Analyzing fine-grained skill activities (e.g., sports, surgery) requires not only recognizing visual patterns but also performing step-by-step visual re

tutorialsarxiv-cs-cv

Learning Complementary Action Modeling from Automotive Maintenance Instructions

arXiv:2606.27808v1 Announce Type: new Abstract: A minute lexical variation can reverse the procedural meaning of an instruction even when the rest of the sentence remains unchanged. In automotive main

Learning to Evict from Key-Value Cache

arXiv:2602.10238v2 Announce Type: replace Abstract: The growing size of Large Language Models (LLMs) makes efficient inference challenging, primarily due to the memory demands of the autoregressive Ke

Mosaic: A Benchmark Suite for Differentiable Physics Solvers

arXiv:2606.27895v1 Announce Type: cross Abstract: Differentiable partial differential equation (PDE) solvers underpin solver-in-the-loop ML training, gradient-based optimal control, and inverse proble

NormAct: A Benchmark for Hidden Social Norm Compliance in Embodied Planning

arXiv:2606.27826v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly deployed as embodied planners in egocentric environments, where task success requires not only

Local Ai

Physics-Guided Robotic Radiation Source Localization along Arbitrary Measurement Paths in Unstructured Environments

arXiv:2606.27624v1 Announce Type: cross Abstract: Using robots to estimate the location of the radiation source is an effective way to improve efficiency and safety. Existing methods focus on planning

local-aiarxiv-cs-lg

Self-Stigma Is Not a Monolith, but Generic Empathy Is: Persona-Conditioned LLM Support for People Who Use Drugs

arXiv:2606.23387v2 Announce Type: replace Abstract: Self-stigma predicts treatment avoidance and disengagement among people who use drugs (PWUD), yet conversational systems aiming to provide support t

StableMotion: One-Step Motion Estimation with Diffusion Prior

arXiv:2505.06668v2 Announce Type: replace Abstract: We present StableMotion, a novel framework that leverages geometric and content priors from pretrained large-scale image diffusion models for motion

researcharxiv-cs-cv

Temporal Convolutional Autoencoder for Interference Mitigation in FMCW Radar Altimeters

arXiv:2505.22783v2 Announce Type: replace-cross Abstract: Reliable altitude estimation with frequency-modulated continuous wave (FMCW) radar altimeters is increasingly a challenge due to in-band inter

researcharxiv-cs-lg

TextDS: Parameter-Efficient Representation Alignment for Scene Text Detection under Distribution Shifts

arXiv:2606.28077v1 Announce Type: new Abstract: In real-world deployments, scene text detectors inevitably face distribution shifts beyond the training distribution. Prior work often depends on large-

Towards Automating Scientific Review with Google's Paper Assistant Tool

arXiv:2606.28277v1 Announce Type: cross Abstract: Artificial intelligence is driving a revolution in scientific discovery, accelerating everything from hypothesis generation to mathematical theorem pr

Tutorials

Towards Reliable Recommender Systems for Rating Data

arXiv:2412.20802v3 Announce Type: replace-cross Abstract: Recommender systems are widely used in the digital landscape to match users with content fitting their preferences. However, growing concerns

tutorialsarxiv-cs-lg

Training-free Truthfulness Detection via Sparse MLP Value Vectors

arXiv:2509.17932v2 Announce Type: replace Abstract: Large language models (LLMs) are prone to generating factually incorrect content, motivating methods for assessing truthfulness from internal model

Two-Stage Fine-Tuning for Protein Sequence Generation with Targeted Amino-Acid Composition

arXiv:2606.27939v1 Announce Type: cross Abstract: Protein language models are standard priors for biological sequence generation, but steering them toward explicit distributional design targets remain

Unified Zero-Shot Time Series Forecasting: A Darts Foundation

arXiv:2606.27438v1 Announce Type: new Abstract: Since its initial release in 2020, Darts has become a widely used open-source Python library for time series analysis. A series of foundation models hav

WARP-RM: A Warp-Augmented Relative Progress Reward Model for Data Curation

arXiv:2606.28320v1 Announce Type: new Abstract: Scaling imitation learning requires large datasets, yet human teleoperation inevitably produces mixed-quality demonstrations containing hesitations and

safetyarxiv-cs-ro

When Search Agents Should Ask: DiscoBench for Clarification-Aware Deep Search

arXiv:2606.27669v1 Announce Type: new Abstract: Search agents powered by large language models (LLMs) are increasingly used to solve complex information-seeking tasks, requiring multi-step retrieval a

ZooClaw-FashionSigLIP2: Distilled Fine-tuning for Robust Fashion Retrieval

arXiv:2606.27708v1 Announce Type: new Abstract: Adapting a foundation vision-language encoder to a specialized retrieval task creates a fundamental tradeoff: gains on the target distribution come at t

Agents

A Guideline-Aware AI Agent for Zero-Shot Target Volume Auto-Delineation

arXiv:2603.09448v2 Announce Type: replace-cross Abstract: Delineating the clinical target volume (CTV) in radiotherapy involves complex margins constrained by tumor location and anatomical barriers. W

agentsarxiv-cs-ai

A Systematic Survey of Semantic Role Labeling in the Era of Pretrained Language Models

arXiv:2502.08660v4 Announce Type: replace Abstract: Semantic role labeling (SRL) is a central natural language processing task for understanding predicate-argument structures within texts and enabling

AgentX: Towards Agent-Driven Self-Iteration of Industrial Recommender Systems

arXiv:2606.26859v1 Announce Type: new Abstract: Recommendation algorithm iteration is moving from an artisanal, engineer-bound process toward an industrialized research loop, but this transition remai

Agents

AlgoEvolve: LLM-driven Meta-evolution of Algorithmic Trading Programs

arXiv:2606.26173v1 Announce Type: new Abstract: Recent work shows that Large Language Models (LLMs) can act as semantic mutation operators for the evolutionary discovery of programs and proofs. Most c

agentsarxiv-cs-ai

Ask, Solve, Generate: Self-Evolving Unified Multimodal Understanding and Generation via Self-Consistency Rewards

arXiv:2606.27376v1 Announce Type: new Abstract: Most unified large multimodal models (LMMs) that support both visual understanding and image generation still rely on curated post-training supervision,

Benchmarking Open-Weight Foundation Models for Global AI Technical Governance

arXiv:2606.26099v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in artificial intelligence (AI) governance analysis across national and international organisat

Beyond Perplexity: UTF-8 Validity in Byte-aware Language Models

arXiv:2606.14122v2 Announce Type: replace Abstract: Byte-level tokenization enables language models to handle any Unicode input, but models can generate invalid UTF-8 sequences when encountering rare

Context Recycling for Long-Horizon LLM Inference

arXiv:2606.26105v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit strong capabilities in short-context reasoning but degrade in performance over long conversational horizons due t

Delegation and Verification Under AI

arXiv:2603.02961v2 Announce Type: replace-cross Abstract: As AI systems enter institutional workflows, workers must decide whether to delegate task execution to AI and how much effort to invest in ver

researcharxiv-cs-ai

E-TTS: A New Embodied Test-Time Scaling Framework for Robotic Manipulation

arXiv:2606.27268v1 Announce Type: cross Abstract: Recently, a few works have made early attempts to study test-time scaling for embodied tasks. However, two major challenges remain unsolved: (1) reaso

Local Ai

Fast LeWorldModel

arXiv:2606.26217v1 Announce Type: cross Abstract: Joint-Embedding Predictive Architectures (JEPAs), including recent LeWorldModel (LeWM), have become a promising foundation for reconstruction-free vis

local-aiarxiv-cs-cv

Graph Reinforcement Learning for Calibration-Aware Quantum Circuit Routing

arXiv:2606.12816v3 Announce Type: replace-cross Abstract: Quantum circuit routing is a key step in compiling programs for noisy intermediate-scale quantum processors. Routes that appear efficient by s

safetyarxiv-cs-lg

Local Ai

Heterogeneous Neural Predictivity from Language Models During Naturalistic Comprehension

arXiv:2606.26880v1 Announce Type: new Abstract: Language-model representations provide structured, high-dimensional annotations of naturalistic language stimuli and can serve as informative neural pre

local-aiarxiv-cs-cl

Highly-recommended reading. Interesting details in this METR's GPT-5.6 eval. They couldn't get a clean capability number because the model c…

Highly-recommended reading. Interesting details in this METR's GPT-5.6 eval. They couldn't get a clean capability number because the model cheated more than any public model they've tested, and even r

model-releasesdair-ai--x

In-Context Model Predictive Generation: Open-Vocabulary Motion Synthesis from Language Models to Physics

arXiv:2606.26981v1 Announce Type: cross Abstract: Synthesizing human motion from textual descriptions is essential for immersive digital applications, yet existing methods face a persistent trade-off

Instruction Bleed: Cross-Module Interference in Prompt-Composed Agentic Systems

arXiv:2606.26356v1 Announce Type: new Abstract: Practitioners of prompt-composed agentic systems report a recurring failure mode: editing one prompt module silently shifts the behavior of others despi

Mean-Field PhiBE: Continuous-Time Mean-Field Reinforcement Learning from Discrete-Time Data

arXiv:2606.26498v1 Announce Type: cross Abstract: This paper addresses model-free continuous-time mean-field control in a setting where the population dynamics evolve continuously according to an unkn

MetaboNet-Bench: A Multi-modal Benchmark for Glucose Forecasting in Type 1 Diabetes

arXiv:2606.18640v2 Announce Type: replace Abstract: Glucose forecasting algorithms are an important aspect of glycemic control management in type 1 diabetes. So far, the research community has develop

Tutorials

Neural Architecture Search for Generative Adversarial Networks: A Comprehensive Review and Critical Analysis

arXiv:2606.26169v1 Announce Type: cross Abstract: Neural Architecture Search (NAS) has emerged as a pivotal technique in optimizing the design of Generative Adversarial Networks (GANs), automating the

tutorialsarxiv-cs-ai

OpenRCA 2.0: From Outcome Labels to Causal Process Supervision

arXiv:2606.27154v1 Announce Type: new Abstract: Root cause analysis (RCA) poses a holistic test of LLM agentic capabilities, such as long-context understanding, multi-step reasoning, and tool use. How

Orthogonal Hierarchical Decomposition for Structure-Aware Table Understanding with Large Language Models

arXiv:2602.01969v2 Announce Type: replace Abstract: Complex tables with multi-level headers, merged cells and heterogeneous layouts pose persistent challenges for LLMs in both understanding and reason

OSC2Runner: OpenSCENARIO 2.x Compliant High-Fidelity AV Simulation in CARLA

arXiv:2606.26533v1 Announce Type: new Abstract: Scenario-Based Testing predominantly relies on the legacy ASAM OpenSCENARIO 1.x XML standard because existing continuous simulation frameworks lack nati

researcharxiv-cs-ro