Search: “models”

Persuasion Should be Double-Blind: A Multi-Domain Dialogue Dataset With Faithfulness Based on Causal Theory of Mind

arXiv:2502.21297v2 Announce Type: replace Abstract: Persuasive dialogue is central to human communication, yet existing datasets often rely on a single language model generating both roles, producing

agentsarxiv-cs-cl

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RAW: Robust Avatar Watermarking -- Benchmarking and Baseline

DGX agent

arXiv:2605.23994v1 Announce Type: cross Abstract: Digital avatar watermarking presents unique challenges: avatars are routinely post-processed with background replacement, reframing, and format conver

model-releasesarxiv-cs-ai

26 May 2026

Refining Context-Entangled Content Segmentation via Curriculum Selection and Anti-Curriculum Promotion

arXiv:2602.01183v2 Announce Type: replace-cross Abstract: Biological learning proceeds from easy to difficult tasks, gradually reinforcing perception and robustness. Inspired by this principle, we add

RePlan-Bot: Multi-Level Replanning for Embodied Instruction Following

model-releasesarxiv-cs-ro

arXiv:2605.25851v1 Announce Type: new Abstract: Embodied instruction following (EIF) requires agents to understand and execute complex natural language commands within interactive 3D environments. Des

Rethinking Continual Anomaly Detection on the Edge: Benchmarking Under Realistic Industrial Conditions

arXiv:2605.24251v1 Announce Type: new Abstract: Continual anomaly detection (CAD) addresses the need for industrial inspection systems to adapt to evolving production conditions, yet existing methods

Right-Sizing Communication and Recommendation Set Size in AI-Assisted Search

arXiv:2605.23944v1 Announce Type: new Abstract: We model the interaction between a user and an AI driven recommendation system. The user initiates the process by conveying preference information throu

Robust inference using density-powered Stein operators

arXiv:2511.03963v2 Announce Type: replace-cross Abstract: We introduce a density-power weighted variant for the Stein operator, called the gamma-Stein operator. This is a novel class of operators deri

Safety-Oriented Routing Analysis of Mixtral MoE Under Benign and Harmful Prompts

arXiv:2605.24270v1 Announce Type: new Abstract: Sparse mixture-of-experts (MoE) language models activate only a small subset of parameters for each token, making router behavior a central part of mode

Scaling up Energy-Aware Multi-Agent Reinforcement Learning for Mission-Oriented Drone Networks with Individual Reward

arXiv:2605.24992v1 Announce Type: cross Abstract: Multi-agent reinforcement learning (MARL) has shown wide applicability in collaborative systems such as autonomous driving and smart cities for its ab

Schema-Grounded LLM Extraction for FHIR Patient Digital Twins

model-releasesarxiv-cs-cl

arXiv:2601.05847v2 Announce Type: replace Abstract: We revisit the problem of constructing interoperable patient digital twins from unstructured electronic health records (EHRs) and argue that the tas

SEAL: Synergistic Co-Evolution of Agents and Learning Environments

arXiv:2605.24426v1 Announce Type: new Abstract: Large Language Model (LLM) agents are increasingly improved through interaction, yet most self-evolution methods adapt either the policy or the learning

safetyarxiv-cs-cl

SMDD-Bench: Can LLMs Solve Real-World Small Molecule Drug Design Tasks?

arXiv:2605.21740v2 Announce Type: replace Abstract: LLM agents have incredible potential for scientific discovery applications. However, the performance of LLM agents on real-world, small molecule dru

Spectral Retrieval: Multi-Scale Sinc Convolution over Token Embeddings for Localized Retrieval in LLM Multi-Agent Systems

arXiv:2605.24764v1 Announce Type: cross Abstract: [Abridged] - Spectral Retrieval is a plug-in re-ranking stage that interpolates between per-token MaxSim and mean-pool retrieval through a multi-scale

Split-Merge: A Difference-based Approach for Dominant Eigenvalue Problem

arXiv:2501.15131v3 Announce Type: replace-cross Abstract: The computation of the dominant eigenpair for symmetric positive semidefinite matrices is fundamental in numerical optimization. This work shi

Stein Variational Ergodic Surface Coverage with SE(3) Constraints

model-releasesarxiv-cs-ro

arXiv:2603.09458v3 Announce Type: replace Abstract: Surface manipulation tasks require robots to generate trajectories that comprehensively cover complex 3D surfaces while maintaining precise end-effe

Stochastic Estimation of the Layer-wise Hessian Trace for Monitoring Neural-network Training

arXiv:2605.25674v1 Announce Type: new Abstract: The loss and the norm of its gradient separate the healthy and the pathological regimes of neural-network training only weakly, whilst the curvature of

Streaming Reinforcement Learning under Partial Observability with Real-Time Recurrent Learning

arXiv:2605.24709v1 Announce Type: new Abstract: Streaming reinforcement learning has emerged as an online learning paradigm that conforms to the restrictions of natural learning agents that process da

Applications

Structure-Aware RAG: Structured Retrieval Augmented Generation from Noisy Data for Conversational Agents

arXiv:2605.24366v1 Announce Type: new Abstract: Large Language Models (LLMs) have been widely adopted in conversational applications. However, their reliance on parametric knowledge limits reliability

applicationsarxiv-cs-cl

Test-Time Deep Thinking to Explore Implicit Rules

arXiv:2605.24828v1 Announce Type: new Abstract: With the continuous advancement of Large Language Models (LLMs), intelligent agents are becoming increasingly vital. However, these agents often fail in

Test-Time Graph Search for Goal-Conditioned Reinforcement Learning

arXiv:2510.07257v2 Announce Type: replace Abstract: Offline goal-conditioned reinforcement learning (GCRL) often struggles with long-horizon tasks, where errors in value estimation accumulate and prod

TGFormer: Towards Temporal Graph Transformer with Auto-Correlation Mechanism

arXiv:2605.24971v1 Announce Type: cross Abstract: The growing interest in Temporal Graph Neural Networks (TGNNs) stems from their ability to model complex dynamics and deliver superior performance. Ho

researcharxiv-cs-ai

The Many Faces of On-Policy Distillation: Pitfalls, Mechanisms, and Fixes

arXiv:2605.11182v2 Announce Type: replace Abstract: On-policy distillation (OPD) and on-policy self-distillation (OPSD) have emerged as promising post-training methods for large language models, offer

The Time is Here for Just-in-Time Systems: Challenges and Opportunities

arXiv:2605.24096v1 Announce Type: cross Abstract: Core systems like key-value stores have historically taken years to build, and are designed to be general so as to amortize cost across deployments, p

The Tokenizer Tax Across 25 European Languages: Domain Invariance, Cross-Lingual Few-Shot Effects, and the Ukrainian Penalty

arXiv:2605.24718v1 Announce Type: new Abstract: Tokenizer fertility the number of tokens per word imposes a hidden cost on non-English NLP. We measure fertility for ten foundation models across 25 Eur

They Are Not the Same: Direct Causes Are Not Grounded Emotion Explanations

arXiv:2605.25208v1 Announce Type: new Abstract: Emotion-Cause Pair Extraction (ECPE) was introduced to explain why an emotion occurs, but this goal is now often reduced to binary pair/non-pair predict

ToolRegistry: A Protocol-Agnostic Tool Management Library for Function-Calling LLMs

arXiv:2507.10593v3 Announce Type: replace-cross Abstract: Every LLM tool call is structurally an RPC -- a function name, JSON arguments, and a serialized result -- yet each protocol (native Python, MC

Toward Reliable Design of LLM-Enabled Agentic Workflows: Optimizing Latency-Reliability-Cost Tradeoffs

arXiv:2605.23929v1 Announce Type: new Abstract: Modern AI systems increasingly rely on workflows composed of multiple interacting agents, some powered by large language models (LLMs) and others by con

Local Ai

Towards Verifiable Transformers: Solver-Checkable Circuit Explanations

arXiv:2605.24033v1 Announce Type: new Abstract: Mechanistic interpretability often identifies circuits inside Transformer models, but explanations of those circuits are usually validated through examp

local-aiarxiv-cs-lg

TRACE: A taxonomy-grounded synthetic dataset for teaching-program generation and session interpretation in Applied Behavior Analysis

model-releasesarxiv-cs-cl

arXiv:2605.25038v1 Announce Type: new Abstract: Applied Behavior Analysis (ABA) is a clinical discipline whose documentation, teaching programs and multi-session behavioral logs, is formulaic and high

Trade-off Functions for DP-SGD with Subsampling based on Random Shuffling: Tight Upper and Lower Bounds

arXiv:2605.06259v2 Announce Type: replace Abstract: We derive a tight analysis of the trade-off function for Differentially Private Stochastic Gradient Descent (DP-SGD) with subsampling based on rando

Applications

Transformers over-extend what humans underlearn: the case of Spanish L-shaped morphome

arXiv:2507.21556v3 Announce Type: replace Abstract: The cognitive reality of irregular morphological patterns has been debated for decades: do speakers extend them to novel forms, or are they lexical

applicationsarxiv-cs-cl

Applications

Translators as Invisible Teachers of AI: Copyright, Translation Memory, and the Political Economy of Linguistic Data

arXiv:2605.24842v1 Announce Type: new Abstract: This paper examines how the labour of translators has been transformed into foundational data capital for the age of artificial intelligence (AI). Trans

applicationsarxiv-cs-cl

Local Ai

Treatment Effect Estimation with Differentiated Networked Effect on Graph Data

arXiv:2605.24358v1 Announce Type: cross Abstract: Estimating individual treatment effect (ITE) from observational graph data is crucial for decision-making in the fields such as commerce and medicine.

local-aiarxiv-cs-ai

Uncertainty Decomposition via Cyclical SG-MCMC and Soft-label Learning for Subjective NLP

arXiv:2605.24773v1 Announce Type: new Abstract: Annotator disagreement in emotion classification reflects ambiguity intrinsic to emotion concepts and is essential for predictor-quality assessment in s

Uncovering Vulnerabilities of LLM-Assisted Cyber Threat Intelligence

arXiv:2509.23573v4 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly used to help security analysts manage the surge of cyber threats, automating tasks from vulnerab

researcharxiv-cs-ai

Local Ai

Unlocking Apple's Private Cloud Compute: An Analysis of Privacy-Preserving Artificial Intelligence

arXiv:2605.24239v1 Announce Type: cross Abstract: Many existing Artificial Intelligence (AI) solutions on mobile devices rely on an extensive collection of sensitive data, raising privacy concerns and

local-aiarxiv-cs-ai

V3H: View Variation and View Heredity for Incomplete Multi-view Clustering

arXiv:2011.11194v4 Announce Type: replace Abstract: Real data often appear in the form of multiple incomplete views. Incomplete multi-view clustering is an effective method to integrate these incomple

VineLM: Trie-Based Fine-Grained Control for Agentic Workflows

arXiv:2605.23914v1 Announce Type: cross Abstract: Agentic workflows interleave configurable LLM stages with tool stages and often include retries or refinement loops. Existing workflow managers profil

Volatility Surface Reconstruction using Deep Learning under No-Arbitrage Constraints

arXiv:2605.24031v1 Announce Type: cross Abstract: We study the reconstruction of implied volatility surfaces from sparse and noisy option quotes using deep learning models under no-arbitrage constrain

When Interpretability Becomes a Liability: Adversarial Attacks on CBM Concept Layers

arXiv:2605.25304v1 Announce Type: new Abstract: Concept Bottleneck Models (CBMs) have emerged as a cornerstone approach for interpretable machine learning, providing human-understandable intermediate

WhenLoss: Diagnosing Write and Retrieval Bottlenecks in Long-Context Memory Systems

model-releasesarxiv-cs-cl

arXiv:2605.24579v1 Announce Type: new Abstract: Long-context memory systems often fail under fixed budgets, but end-to-end evaluation does not reveal whether evidence was discarded during compression

Word Class Representations Spontaneously Emerge from Successor Representations Trained on Natural Language

arXiv:2605.24585v1 Announce Type: new Abstract: Language models are typically trained to predict the next token in a sequence. Here, we explore an alternative predictive principle from reinforcement l

A measurement substrate for agentic Kubernetes operations: Methodology and a case study in retrieval-compounding falsification

arXiv:2605.23058v1 Announce Type: cross Abstract: Empirical claims about autonomous Kubernetes operations agents are largely unfalsifiable. Published work reports observational results without control

Agentic Proving for Program Verification

arXiv:2605.23772v1 Announce Type: new Abstract: Agentic systems have recently emerged as state-of-the-art approaches for automated theorem proving in formal mathematics. To assess how far these capabi

AI Assurance: A Comprehensive Testing Strategy for Enterprise AI Systems

arXiv:2605.23459v1 Announce Type: cross Abstract: Enterprise AI systems, built on large language models, retrieval pipelines and autonomous agents, introduce a class of risks that traditional software

AI-Friendly LaTeX: Using LaTeX Code as a Knowledge Source for Retrieval-Augmented Generation

arXiv:2605.22923v1 Announce Type: cross Abstract: Large language models can answer questions about textbooks, lecture notes, and programming exercises more reliably when their answers are grounded in

ArcMark: Distortion-Free Multi-Byte LLM Watermark via Optimal Transport

arXiv:2602.07235v2 Announce Type: replace-cross Abstract: Watermarking is an important tool for promoting the responsible use of large language models (LLMs). Existing watermarks insert a signal into

researcharxiv-cs-ai

Are Targeted Data Poisoning Attacks as Effective as We Think?

arXiv:2509.06896v2 Announce Type: replace Abstract: Targeted data poisoning attacks manipulate model predictions on specific test samples by injecting malicious data into training. Yet existing evalua