Search: “papers”

Early Diagnosis of Wasted Computation in Multi-Agent LLM Systems via Failure-Aware Observability

arXiv:2606.01365v1 Announce Type: new Abstract: Tool-using multi-agent large language model (LLM) systems spend computation through model tokens, tool calls, retries, and code execution before produci

agentsarxiv-cs-ai

Agents

Easier to Mislead Than to Correct: Harmful and Beneficial Revision in LLM Conformity

DGX agent

arXiv:2606.01637v1 Announce Type: cross Abstract: Large language models are increasingly used in multi-agent systems, where they see and respond to other agents' answers. A key risk is conformity: a m

agentsarxiv-cs-ai

2 Jun 2026

EEG-FuseFormer: A Transformer-Driven Feature Fusion Framework for Seizure Onset Prediction

arXiv:2606.02166v1 Announce Type: new Abstract: Epilepsy is one of the most common neurological disorders globally, characterized by recurring seizures and significantly impacting the quality of life.

Efficient Synthetic Network Generation via Latent Embedding Reconstruction

arXiv:2606.00934v1 Announce Type: cross Abstract: Network data are ubiquitous across the social sciences, biology, and information systems. Generating realistic synthetic network data has broad applic

Efficient Test-time Inference for Generative Planning Models

arXiv:2606.00618v1 Announce Type: new Abstract: Generative models have emerged as a powerful paradigm for AI planning, yet their performance remains constrained by the training data distribution. One

Enhancing Blind Source Separation with Dissociative Principal Component Analysis

model-releasesarxiv-cs-cv

arXiv:2411.12321v2 Announce Type: replace Abstract: Principal component analysis (PCA) and its sparse variants (sPCA) are widely used as a precursor to independent component analysis (ICA) for blind s

EuroBERT: Scaling Multilingual Encoders for European Languages

arXiv:2503.05500v3 Announce Type: replace-cross Abstract: General-purpose multilingual vector representations, used in retrieval, regression and classification, are traditionally obtained from bidirec

Evaluating the Reversal Curse in Model Editing

arXiv:2310.10322v3 Announce Type: replace Abstract: Large language models (LLMs) are prone to hallucinate unintended text due to false or outdated knowledge. Since retraining LLMs is resource intensiv

Evaluation of Baseline Methods for IDD-based SSD External Memory Search

arXiv:2606.01840v1 Announce Type: new Abstract: Many difficult search problems cannot be solved by algorithms such as A* using only RAM. Search algorithms which use external memory such as SSDs and HD

Explainable Data-driven Deep Reinforcement Learning Methods for Optimal Energy Management in Buildings

arXiv:2606.02049v1 Announce Type: new Abstract: The increasing integration of renewable energy sources into power systems, particularly in buildings equipped with photovoltaic (PV) panels and energy s

Extending Causal Metamodeling to a non-Markovian Queue

arXiv:2606.00795v1 Announce Type: cross Abstract: Metamodels for discrete-event simulations approximate the behavior of simulation models without running expensive simulations. Prior work introduced m

ext{VG}^2GT: Voxel-Gaussian Splatting Visual Geometry Grounded Transformer

arXiv:2606.01573v1 Announce Type: new Abstract: Gaussian splatting has shown strong potential for 3D reconstruction and novel view synthesis. However, most existing methods require accurate camera par

researcharxiv-cs-cv

Local Ai

FDIO: Frequency Decomposed Inertial Odometry

arXiv:2511.15645v3 Announce Type: replace Abstract: Pedestrian inertial odometry (PIO) estimates autonomous pedestrian motion using only acceleration and angular velocity measurements collected by an

local-aiarxiv-cs-cv

Feature Alignment Determines Fusion Strategy: A Comparative Study of Cross-Attention and Concatenation in Multimodal Learning

arXiv:2606.01207v1 Announce Type: new Abstract: The choice between cross-attention and concatenation for multimodal fusion remains governed by practitioner intuition rather than principled understandi

safetyarxiv-cs-cv

FedS2R: One-Shot Federated Domain Generalization for Synthetic-to-Real Semantic Segmentation in Autonomous Driving

arXiv:2507.19881v2 Announce Type: replace-cross Abstract: Federated domain generalization has shown promising progress in image classification by enabling collaborative training across multiple client

agentsarxiv-cs-ai

Tutorials

Finding What Matters: Anchoring Context Knowledge with Evolving Indices for Iterative Retrieval

arXiv:2601.16462v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) has become a dominant paradigm for mitigating hallucinations in Large Language Models (LLMs) by incorporating e

tutorialsarxiv-cs-cl

Finer Parameter Steps for Low-Rank PEFT: A Controlled Study with CP Tensor Adapters

arXiv:2606.00428v1 Announce Type: cross Abstract: Low-rank adapters are usually compared by sweeping a small set of ranks, but the rank also fixes the resolution of the parameter budget. For a 2048{im

Fixed Budget is No Harder Than Fixed Confidence in Best-Arm Identification up to Logarithmic Factors

arXiv:2602.03972v3 Announce Type: replace-cross Abstract: The best-arm identification (BAI) problem is one of the most fundamental problems in interactive machine learning, which has two flavors: the

FlowOVD: Learning Generative Latent Flows for Zero-shot Open-vocabulary Detection

model-releasesarxiv-cs-cv

arXiv:2606.00782v1 Announce Type: new Abstract: Open-vocabulary object detection (OVD) has achieved remarkable progress through large-scale vision-language pre-training. Existing methods, however, typ

Food Noise & False Safety: A Systematic Evaluation of How LLMs Fail to Adapt to Eating Disorder Queries with Clinician Feedback

arXiv:2606.02444v1 Announce Type: new Abstract: Recent evidence shows that people with eating disorders (EDs) are increasingly seeking guidance, advice, and emotional support from Large Language Model

ForeSci: Evaluating LLM Agents for Forward-Looking AI Research Judgment

arXiv:2606.00644v1 Announce Type: new Abstract: AI research often requires decisions before future evidence exists: which bottleneck to attack, which direction to pursue, or where a project should be

From Cues to Horizons: Dynamic Risk Horizon Profiling for Trajectory Prediction

arXiv:2606.00857v1 Announce Type: cross Abstract: Accurate and reliable vehicle trajectory prediction is essential for safe autonomous driving. Recent studies have incorporated safety risk into trajec

From Global to Local: Learning Context-Aware Graph Representations for Document Classification and Summarization

arXiv:2603.00021v2 Announce Type: replace Abstract: Recent NLP systems commonly represent documents as linear token sequences. Although this captures sequential order, it can hinder modeling long-rang

researcharxiv-cs-cl

Applications

From Human Videos to Robot Manipulation: A Survey on Scalable Vision-Language-Action Learning with Human-Centric Data

arXiv:2606.00054v1 Announce Type: cross Abstract: Recent progress in generalizable embodied control has been driven by large-scale pretraining of Vision-Language-Action (VLA) models. However, most exi

applicationsarxiv-cs-ai

Generalization Limits in Vehicle Re-Identification

arXiv:2606.01981v1 Announce Type: new Abstract: Vehicle re-identification focuses on retrieving images of the same vehicle from a gallery given a query image. Upon closer inspection of commonly used d

researcharxiv-cs-cv

Generative AI and Digital Ecosystem Resilience: A Proactive Lifecycle-Based Survey

arXiv:2606.00136v1 Announce Type: cross Abstract: The proliferation of adversarial synthetic content, accelerated by Generative AI (GenAI) is rendering traditional reactive detection methods ineffecti

agentsarxiv-cs-ai

Generative Multi-Robot Motion Planning via Diffusion Modeling with Multi-Agent Reinforcement Learning Guidance

arXiv:2606.00933v1 Announce Type: new Abstract: Coordinating multiple robots in shared environments requires generating feasible trajectories for each agent while accounting for interactions among age

agentsarxiv-cs-ro

Geometric Latent Reasoning Induces Shorter Generations in LLMs

arXiv:2606.02248v1 Announce Type: new Abstract: Large language models solve complex problems by generating lengthy chains of explicit reasoning tokens. While effective, this makes reasoning expensive,

researcharxiv-cs-cl

GeoSAM-3D: Geodesic Prompt Propagation for Open-Vocabulary 3D Scene Segmentation from Monocular Video

arXiv:2606.00447v1 Announce Type: cross Abstract: Open-vocabulary 3D scene segmentation usually assumes RGB-D video, calibrated multi-view imagery, or a reconstructed mesh. GeoSAM-3D studies a lighter

GFlowGR: Fine-tuning Generative Recommendation Frameworks with Generative Flow Networks

arXiv:2506.16114v3 Announce Type: replace-cross Abstract: Generative recommendations (GR), which usually include item tokenizers and generative Large Language Models (LLMs), have demonstrated remarkab

Global PIQA: Evaluating Commonsense Reasoning Across 100+ Languages and Cultures

arXiv:2510.24081v2 Announce Type: replace Abstract: To date, there exist almost no culturally-specific evaluation benchmarks for large language models (LLMs) that cover a large number of languages and

GloResNet: A lightweight 3D CNN with global topological features for preterm brain injury prediction

arXiv:2606.02498v1 Announce Type: new Abstract: This study introduces an automated deep learning framework for predicting brain injury (BI) in preterm infants from T2-weighted MRI (dHCP dataset). We p

researcharxiv-cs-cv

GPTQ-intrinsic LoRA: A Near-optimal Algorithm for Low-precision Quantization with Low-rank Adaptation

arXiv:2606.01412v1 Announce Type: new Abstract: Post-training quantization is widely used for compressing large neural networks, but aggressive low-bit quantization can significantly degrade model qua

Applications

Graph-Augmented Retrieval for Cross-Entity Financial Sentiment Analysis: A Comparative Study

arXiv:2606.00062v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become foundational for grounding large language models in domain-specific corpora, yet conventional vector-bas

applicationsarxiv-cs-cl

Graph is a Natural Regularization: Revisiting Vector Quantization for Graph Representation Learning

arXiv:2508.06588v3 Announce Type: replace-cross Abstract: Vector Quantization (VQ) has recently emerged as a promising approach for learning compressed and discrete representations for graph-structure

HAIM: Human-AI Music Datasets for AI Music Production Tracking Benchmark

arXiv:2606.01686v1 Announce Type: cross Abstract: As generative platforms such as Suno and Udio reach human-grade audio quality, the scope of AI's utility has expanded across the entire music producti

Hierarchical Online Prompt Mutation with Dual-Loop Feedback for Guardrailed Evidence Document Generation: A Production-Evaluation Case Study

arXiv:2606.01472v1 Announce Type: cross Abstract: High-stakes production document-generation systems require language models to be adaptive, evidence-grounded, and auditable. We present HOPM, a hierar

How AI Fails: An Interactive Pedagogical Tool for Demonstrating Dialectal Bias in Automated Toxicity Models

arXiv:2511.06676v3 Announce Type: replace Abstract: Now that AI-driven moderation has become pervasive in everyday life, we often hear claims that 'the AI is biased'. While this is often said jokingly

How Much Progress Has There Been in NVIDIA Datacenter GPUs?

arXiv:2601.20115v3 Announce Type: replace-cross Abstract: As the role of modern Graphics Processing Units (GPUs) becomes increasingly essential for several computing tasks, analyzing their past and cu

Local Ai

HRTFformer: A Spatially-Aware Transformer for Individual HRTF Upsampling in Immersive Audio Rendering

arXiv:2510.01891v2 Announce Type: replace-cross Abstract: Individual Head-Related Transfer Functions (HRTFs) are starting to be introduced in many commercial immersive audio applications and are cruci

local-aiarxiv-cs-ai

Hybrid TD3: Overestimation Bias Analysis and Stable Policy Optimization for Hybrid Action Space

arXiv:2603.01302v2 Announce Type: replace Abstract: Reinforcement learning in discrete-continuous hybrid action spaces presents fundamental challenges for robotic manipulation, where high-level task d

safetyarxiv-cs-ro

HypothesisMed: Inference-Time Answer Fusion and Structured Hypothesis-Space Reporting for Biomedical Question Answering

arXiv:2606.00971v1 Announce Type: new Abstract: Biomedical question answering with large language models is commonly evaluated using answer accuracy, but answer accuracy alone does not indicate whethe

'I Strongly Suspect This Website Is a Scam': Benchmarking PII Leakage and Detection without Defense in Autonomous Web Agents

arXiv:2606.00497v1 Announce Type: cross Abstract: Deceptive web content, widely instantiated across the internet and commonly known as extit{social-engineering attacks}, manipulates autonomous web age

iML: Executable, Problem-Grounded, and Broadly Exploratory Code-Driven AutoML

arXiv:2602.13937v2 Announce Type: replace Abstract: Automated Machine Learning (AutoML) has improved access to machine learning, yet existing techniques often remain limited in flexibility, transparen

agentsarxiv-cs-lg

Improved Belief-Attention in Vision Task

arXiv:2606.00077v1 Announce Type: cross Abstract: Recently, Belief-Attention ite{Guoqiang25BeliefAttention} has been proposed by first performing an orthogonal projection of the softmax-based weighted

IndoBias: A Dual Track Culturally Grounded Benchmark for LLMs Bias Evaluation in Indonesian Languages

arXiv:2606.01260v1 Announce Type: cross Abstract: Despite being home to more than 1300 ethnic groups and 700 indigenous languages, bias in Large Language Models has not been fully studied in Indonesia

Interpretability in Deep Time Series Models Demands Semantic Alignment

arXiv:2602.02239v2 Announce Type: replace Abstract: Deep time series models continue to improve predictive performance, yet their deployment remains limited by their black-box nature. In response, exi

safetyarxiv-cs-lg

Interpretable Graph Kolmogorov-Arnold Networks for Multi-Cancer Classification and Biomarker Identification using Multi-Omics Data

arXiv:2503.22939v4 Announce Type: replace Abstract: The integration of heterogeneous multi-omics datasets at a systems level remains a central challenge for developing analytical and computational mod