Search: “evaluation”

Hammer and Anvil: Toward a Theory of Backdoors in Federated Learning

arXiv:2509.08089v2 Announce Type: replace Abstract: Federated Learning (FL) enables distributed model training but is vulnerable to backdoor attacks, where malicious clients embed attacker-controlled

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Model Releases

HyperEyes: Dual-Grained Efficiency-Aware Reinforcement Learning for Parallel Multimodal Search Agents

DGX agent

arXiv:2605.07177v1 Announce Type: cross Abstract: Existing multimodal search agents process target entities sequentially, issuing one tool call per entity and accumulating redundant interaction rounds

model-releasesarxiv-cs-ai

11 May 2026

ICDAR 2026 Competition on Writer Identification and Pen Classification from Hand-Drawn Circles

arXiv:2605.07816v1 Announce Type: new Abstract: This paper presents CircleID, a large-scale ICDAR 2026 competition on writer identification and pen classification from scanned hand-drawn circles. The

researcharxiv-cs-cv

Tutorials

Inductive Power Grid Cascading Failure Analysis with GRU-Gated Graph Attention

arXiv:2605.07010v1 Announce Type: new Abstract: Identifying vulnerable transmission lines in power grids before a cascading failure occurs is challenging: existing methods can learn inter-line failure

tutorialsarxiv-cs-lg

Inverse Reinforcement Learning with Just Classification and a Few Regressions

arXiv:2509.21172v2 Announce Type: replace Abstract: Inverse reinforcement learning (IRL) aims to infer rewards from observed behavior, but rewards are not identified from the policy alone: many reward

safetyarxiv-cs-lg

LLM-Based Agents for Competitive Landscape Mapping in Drug Asset Due Diligence

arXiv:2508.16571v4 Announce Type: replace Abstract: In this paper, we describe and benchmark a competitor-discovery component used within an agentic AI system for fast drug asset due diligence. A comp

LLM-Guided Open Hypothesis Learning from Autonomous Scanning Probe Microscopy Experiments

arXiv:2605.06839v1 Announce Type: cross Abstract: Autonomous experimentation has transformed microscopy and materials discovery by enabling closed-loop optimization including imaging and spectroscopy

agentsarxiv-cs-ai

MASPO: Joint Prompt Optimization for LLM-based Multi-Agent Systems

arXiv:2605.06623v1 Announce Type: cross Abstract: Large language model (LLM)-based Multi-agent systems (MAS) have shown promise in tackling complex collaborative tasks, where agents are typically orch

agentsarxiv-cs-lg

MatryoshkaLoRA: Learning Accurate Hierarchical Low-Rank Representations for LLM Fine-Tuning

arXiv:2605.07850v1 Announce Type: cross Abstract: With the rise in scale for deep learning models to billions of parameters, the computational cost of fine-tuning remains a significant barrier to depl

Applications

MinMax Recurrent Neural Cascades

arXiv:2605.06384v2 Announce Type: replace-cross Abstract: We show that the MinMax algebra provides a form of recurrence that is expressively powerful, efficiently implementable, and most importantly i

applicationsarxiv-cs-ai

MIPIAD: Multilingual Indirect Prompt Injection Attack Defense with Qwen -- TF-IDF Hybrid and Meta-Ensemble Learning

arXiv:2605.07269v1 Announce Type: new Abstract: Indirect prompt injection remains a persistent weakness in retrieval-augmented and tool-using LLM systems, and the problem becomes harder to characteris

MobileDev-Bench: A Benchmark for Issue Resolution in Mobile Application Development

model-releasesarxiv-cs-lg

arXiv:2603.24946v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown strong performance on automated software engineering tasks, yet existing benchmarks focus primarily on

ModelLens: Finding the Best for Your Task from Myriads of Models

model-releasesarxiv-cs-lg

arXiv:2605.07075v1 Announce Type: new Abstract: The open-source model ecosystem now contains hundreds of thousands of pretrained models, yet picking the best model for a new dataset is increasingly in

Not All Tokens Need 40 Steps: Heterogeneous Step Allocation in Diffusion Transformers for Efficient Video Generation

arXiv:2605.06892v1 Announce Type: new Abstract: Diffusion Transformers (DiTs) have achieved state-of-the-art video generation quality, but they incur immense computational cost because standard infere

researcharxiv-cs-cv

Tutorials

Open-Ended Task Discovery via Bayesian Optimization

arXiv:2605.07572v1 Announce Type: new Abstract: When applying Bayesian optimization (BO) to scientific workflow, a major yet often overlooked source of uncertainty is the task itself -- namely, what t

tutorialsarxiv-cs-ai

Optimal Experiments for Partial Causal Effect Identification

arXiv:2605.06993v1 Announce Type: new Abstract: Causal queries are often only partially identifiable from observational data, and experiments that could tighten the resulting bounds are typically cost

Overcoming data scarcity through multi-center federated learning for organs-at-risk segmentation in pediatric upper abdominal radiotherapy

arXiv:2605.06820v1 Announce Type: cross Abstract: Deep learning-based organs/structures-at-risk(OARs) auto-contouring models can improve radiotherapy workflows, but models trained on adult data often

local-aiarxiv-cs-ai

Physical Simulators as Do-Operators: Causal Discovery under Latent Confounders for AI-for-Science

arXiv:2605.07467v1 Announce Type: cross Abstract: Existing interventional causal discovery methods -- IGSP, DCDI, ENCO -- assume causal sufficiency (no latent confounders) and rely on virtual interven

safetyarxiv-cs-ai

PhySPRING: Structure-Preserving Reduction of Physics-Informed Twins via GNN

model-releasesarxiv-cs-ro

arXiv:2605.07687v1 Announce Type: new Abstract: Physics-based digital twins aim to predict the dynamics of real-world objects under interaction, enabling real-to-sim-to-real applications in robotics.

Privately Estimating Black-Box Statistics

arXiv:2510.00322v3 Announce Type: replace-cross Abstract: Standard techniques for differentially private estimation, such as Laplace or Gaussian noise addition, require guaranteed bounds on the sensit

ProactiveMobile: A Comprehensive Benchmark for Boosting Proactive Intelligence on Mobile Devices

arXiv:2602.21858v4 Announce Type: replace Abstract: Multimodal large language models (MLLMs) have made significant progress in mobile agent development, yet their capabilities are predominantly confin

Qwen3-VL-Seg: Unlocking Open-World Referring Segmentation with Vision-Language Grounding

arXiv:2605.07141v1 Announce Type: cross Abstract: Open-world referring segmentation requires grounding unconstrained language expressions to precise pixel-level regions. Existing multimodal large lang

RedDiffuser: Auditing Multimodal Safety Failures in Vision-Language Models via Reinforced Diffusion

model-releasesarxiv-cs-cv

arXiv:2503.06223v5 Announce Type: replace Abstract: Large Vision-Language Models (VLMs) are increasingly deployed in open-ended environments, where ensuring reliable safety under multimodal inputs is

Reflections and New Directions for Human-Centered Large Language Models

arXiv:2605.06901v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly shaping the private and professional lives of users, with numerous applications in business, education, fi

safetyarxiv-cs-cl

SCOPE: Structured Decomposition and Conditional Skill Orchestration for Complex Image Generation

arXiv:2605.08043v1 Announce Type: cross Abstract: While text-to-image models have made strong progress in visual fidelity, faithfully realizing complex visual intents remains challenging because many

Applications

Script Sensitivity: Benchmarking Language Models on Unicode, Romanized and Mixed-Script Sinhala

arXiv:2601.14958v3 Announce Type: replace-cross Abstract: The performance of Language Models (LMs) on low-resource, morphologically rich languages like Sinhala remains largely unexplored, particularly

applicationsarxiv-cs-ai

Semantic State Abstraction Interfaces for LLM-Augmented Portfolio Decisions: Multi-Axis News Decomposition and RL Diagnostics

arXiv:2605.06730v1 Announce Type: new Abstract: We introduce Semantic State Abstraction Interfaces (SSAI): a methodological template for mapping sparse unstructured text into K auditable, named coordi

Sensitivity-Based Robust NMPC for Close-Proximity Offshore Wind Turbine Inspection with a Tilted Multirotor

arXiv:2605.07771v1 Announce Type: new Abstract: Close-proximity offshore wind turbine inspection requires strict clearance control around large cylindrical structures under wind and model mismatch. No

safetyarxiv-cs-ro

SteelDefectX: A Multi-Form Vision-Language Dataset and Benchmark for Steel Surface Defect Analysis

arXiv:2603.21824v2 Announce Type: replace-cross Abstract: Steel surface defect analysis is critical for industrial quality control, yet existing benchmarks rely primarily on label-only annotations, li

Tutorials

Tables Guide Vision: Learning to See the Heart through Tabular Data

arXiv:2503.14998v3 Announce Type: replace Abstract: Contrastive learning methods in computer vision typically rely on augmented views of the same image or multimodal pretraining strategies that align

tutorialsarxiv-cs-cv

Tools as Continuous Flow for Evolving Agentic Reasoning

arXiv:2605.07339v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in orchestrating tools for reasoning tasks. However, existing methods rely on a s

Topology-Enhanced Alignment for Large Language Models: Trajectory Topology Loss and Topological Preference Optimization

arXiv:2605.07172v1 Announce Type: new Abstract: Alignment of large language models (LLMs) via SFT and RLHF/DPO typically ignores the global geometry of the representation space, relying instead on loc

local-aiarxiv-cs-cl

TRACE: Tourism Recommendation with Accountable Citation Evidence

arXiv:2605.07677v1 Announce Type: cross Abstract: Tourism is a high-stakes setting for conversational recommender systems (CRS): a plausible-sounding suggestion can waste real money and trip time once

researcharxiv-cs-ai

TRACE: Transport Alignment Conformal Prediction via Diffusion and Flow Matching Models

arXiv:2605.07100v1 Announce Type: cross Abstract: Constructing valid and informative conformal prediction regions for multi-dimensional outputs remains a fundamental challenge. While conformal predict

safetyarxiv-cs-lg

UNCOM: Zero-shot Context-Aware Command Understanding for Tabletop Scenarios

arXiv:2410.06355v3 Announce Type: replace-cross Abstract: This paper presents UNCOM, a novel hybrid framework for interpreting natural human commands in tabletop scenarios. The system integrates multi

Understanding Robustness of Model Editing in Code LLMs

model-releasesarxiv-cs-lg

arXiv:2511.03182v2 Announce Type: replace-cross Abstract: Large language models (LLMs) for code are increasingly used in software development, but they remain static after pretraining while APIs and s

VecCISC: Improving Confidence-Informed Self-Consistency with Reasoning Trace Clustering and Candidate Answer Selection

arXiv:2605.08070v1 Announce Type: new Abstract: A standard technique for scaling inference-time reasoning is Self-Consistency, whereby multiple candidate answers are sampled from an LLM and the most c

researcharxiv-cs-ai

Video Understanding Reward Modeling: A Robust Benchmark and Performant Reward Models

arXiv:2605.07872v1 Announce Type: cross Abstract: Multimodal reward models have advanced substantially in text and image domains, yet progress in video understanding reward modeling remains severely l

When Are Experts Misrouted? Counterfactual Routing Analysis in Mixture-of-Experts Language Models

arXiv:2605.07260v1 Announce Type: cross Abstract: Mixture-of-Experts (MoE) language models route each token to a small subset of experts, but whether the routes selected by a trained top-k router are

When Does Critique Improve AI-Assisted Theoretical Physics? SCALAR: Structured Critic--Actor Loop for Agentic Reasoning

arXiv:2605.06772v1 Announce Type: new Abstract: As large language models (LLMs) show increasing promise on research-level physics reasoning tasks and agentic AI becomes more common, a practical questi

When Does Embedding Magnitude Matter? A Cross-Task Functional-Symmetry Framework

arXiv:2602.09229v3 Announce Type: replace Abstract: Cosine similarity normalizes both sides; dot product normalizes neither. We propose a 2x2 framework that independently controls query-side and docum

When Routine Chats Turn Toxic: Unintended Long-Term State Poisoning in Personalized Agents

arXiv:2605.06731v1 Announce Type: cross Abstract: Personalized LLM agents maintain persistent cross-session state to support long-horizon collaboration. Yet, this persistence introduces a subtle but c

Artificial Analysis needs to address HiDream-01 Benchmarks

local-air-stablediffusion

HiDream-O1-Image debuted at #8 in the Artificial Analysis Text to Image Arena , and the Reddit post likely discusses whether this benchmark inclusion and ranking adequately reflect HiDream-01's perfor

10 May 2026

The future of Math is mathematicians and AI agents working together. Very pleased to introduce @GoogleDeepMind's AI co-mathematician: a mult…

The future of Math is mathematicians and AI agents working together. Very pleased to introduce @GoogleDeepMind's AI co-mathematician: a multi-agent system designed to actively collaborate with human e

agentsgary-marcus--x

8 May 2026

Conceptors for Semantic Steering

arXiv:2605.04980v1 Announce Type: cross Abstract: Activation-based steering provides control of LLM behavior at inference time, but the dominant paradigm reduces each concept to a single direction who

Concurrence of Symmetry Breaking and Nonlocality Phase Transitions in Diffusion Models

arXiv:2605.04830v1 Announce Type: new Abstract: Diffusion models undergo a phase transition in a critical time window during generation dynamics, with two complementary diagnoses of criticality. The s

local-aiarxiv-cs-lg

cotomi Act: Learning to Automate Work by Watching You

arXiv:2605.03231v1 Announce Type: new Abstract: What if a browser agent could learn your work simply by watching you do it? We present cotomi Act, a browser-based computer-using agent that combines re

agentsarxiv-cs-ai

Demystifying Manifold Constraints in LLM Pre-training

arXiv:2605.04418v1 Announce Type: new Abstract: The empirical success of large language model (LLM) pre-training relies heavily on heuristic stabilization techniques, such as explicit normalization la