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Beyond Thinking: Imagining in 360^irc for Humanoid Visual Search

arXiv:2605.09146v1 Announce Type: new Abstract: Humanoid Visual Search (HVS) requires agents to actively explore immersive 360^irc environments. While prior methods treat this as a monolithic task rel

researcharxiv-cs-cv

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Beyond Toy Benchmarks: A Systematic Evaluation of OOD Detection Methods For Plant Pathology Classification

DGX agent

arXiv:2605.08618v1 Announce Type: new Abstract: Out-of-distribution (OOD) detection is essential for reliable deployment of deep learning systems, yet the majority of existing methods are evaluated on

model-releasesarxiv-cs-cv

12 May 2026

Local Ai

Beyond ViT Tokens: Masked-Diffusion Pretrained Convolutional Pathology Foundation Model for Cell-Level Dense Prediction

arXiv:2605.08276v1 Announce Type: new Abstract: Cell-level dense prediction is central to computational pathology, but remains challenging due to fine-grained histological structures, strong domain sh

local-aiarxiv-cs-cv

BGG: Bridging the Geometric Gap between Cross-View images by Vision Foundation Model Adaptation for Geo-Localization

model-releasesarxiv-cs-cv

arXiv:2605.10345v1 Announce Type: new Abstract: Geometric differences between cross-view images, such as drone and satellite views, significantly increase the challenge of Cross-View Geo-Localization

Bi-CoG: Bi-Consistency-Guided Self-Training for Vision-Language Models

arXiv:2510.20477v2 Announce Type: replace Abstract: Exploiting unlabeled data through semi-supervised learning (SSL) or leveraging pre-trained models via fine-tuning are two prevailing paradigms for a

safetyarxiv-cs-lg

Bias by Necessity: Impossibility Theorems for Sequential Processing with Convergent AI and Human Validation

arXiv:2605.08716v1 Announce Type: new Abstract: Are certain cognitive biases mathematically inevitable consequences of sequential information processing? We prove that primacy effects, anchoring, and

BiAxisAudit: A Novel Framework to Evaluate LLM Bias Across Prompt Sensitivity and Response-Layer Divergence

model-releasesarxiv-cs-cl

arXiv:2605.09041v1 Announce Type: new Abstract: Bias audits of large language models now operate within governance frameworks such as the EU AI Act, making benchmark reliability a security concern in

Big AI is accelerating the metacrisis: What can we do?

arXiv:2512.24863v2 Announce Type: replace-cross Abstract: The world is in the grip of ecological, meaning, and language crises that are converging into a metacrisis. Big AI is accelerating them all. L

Bilinear autoencoders find interpretable manifolds

arXiv:2605.08891v1 Announce Type: new Abstract: Sparse autoencoders have become a standard tool for uncovering interpretable latent representations in neural networks. Yet salient concepts often span

Biological Plausibility and Representational Alignment of Feedback Alignment in Convolutional Networks

arXiv:2605.08564v1 Announce Type: new Abstract: The feedback alignment (FA) algorithm offers a biologically plausible alternative to backpropagation (BP) for training neural networks yet notably fails

Applications

Biosignal Fingerprinting: A Cross-Modal PPG-ECG Foundation Model

arXiv:2605.09579v1 Announce Type: cross Abstract: Cardiovascular disease remains the leading cause of global mortality, yet scalable cardiac monitoring is hindered by the gap between diagnostic-rich E

applicationsarxiv-cs-ai

Black-Box Detection of LLM-Generated Text Using Generalized Jensen-Shannon Divergence

arXiv:2510.07500v2 Announce Type: replace Abstract: We study black-box detection of machine-generated text under practical constraints: the scoring model (proxy LM) may mismatch the unknown source mod

researcharxiv-cs-lg

Block-Wise Differentiable Sinkhorn Attention: Tail-Refinement Gradients with a Gap-Aware Dustbin Bridge

arXiv:2605.08123v1 Announce Type: cross Abstract: We study long-context balanced entropic optimal transport (OT) attention on TPU hardware through a stopped-base, fixed-depth tail-refinement surrogate

safetyarxiv-cs-cl

BONSAI: Bayesian Optimization with Natural Simplicity and Interpretability

arXiv:2602.07144v2 Announce Type: replace-cross Abstract: Bayesian optimization (BO) is a popular technique for sample-efficient optimization of black-box functions. In many applications, the paramete

BoostAPR: Boosting Automated Program Repair via Execution-Grounded Reinforcement Learning with Dual Reward Models

arXiv:2605.09134v1 Announce Type: new Abstract: Reinforcement learning for program repair is hindered by sparse execution feedback and coarse sequence-level rewards that obscure which edits actually f

BoostLLM: Boosting-inspired LLM Fine-tuning for Few-shot Tabular Classification

arXiv:2605.06117v2 Announce Type: replace Abstract: Large language models (LLMs) have recently been adapted to tabular prediction by serializing structured features into natural language, but their pe

Break the Brake, Not the Wheel: Untargeted Jailbreak via Entropy Maximization

arXiv:2605.10764v1 Announce Type: cross Abstract: Recent studies show that gradient-based universal image jailbreaks on vision-language models (VLMs) exhibit little or no cross-model transferability,

Breaking Contextual Inertia: Reinforcement Learning with Single-Turn Anchors for Stable Multi-Turn Interaction

arXiv:2603.04783v2 Announce Type: replace Abstract: While LLMs demonstrate strong reasoning capabilities when provided with full information in a single turn, they exhibit substantial vulnerability in

Breaking the Grid: Distance-Guided Reinforcement Learning in Large Discrete Action Spaces

arXiv:2602.08616v2 Announce Type: replace-cross Abstract: Reinforcement Learning (RL) is increasingly applied to large-scale decision-making problems like logistics, scheduling, and recommender system

Breaking the Impasse: Dual-Scale Evolutionary Policy Training for Social Language Agents

arXiv:2605.08721v1 Announce Type: new Abstract: While Reinforcement Learning with Verifiable Rewards (RLVR) has proven effective for closed-ended tasks, extending it to open-ended social language game

safetyarxiv-cs-cl

Breaking the Reward Barrier: Accelerating Tree-of-Thought Reasoning via Speculative Exploration

arXiv:2605.10195v1 Announce Type: new Abstract: Tree-of-Thought (ToT) reasoning structures Large Language Model (LLM) inference as a tree-based search, demonstrating strong potential for solving compl

researcharxiv-cs-lg

BRIDGE: Building Representations In Domain Guided Program Synthesis

arXiv:2511.21104v3 Announce Type: replace Abstract: Large language models can generate plausible code, but remain brittle for formal verification in proof assistants such as Lean. A central scalabilit

safetyarxiv-cs-lg

Bridging Modalities, Spanning Time: Structured Memory for Ultra-Long Agentic Video Reasoning

arXiv:2605.08271v1 Announce Type: cross Abstract: Understanding ultra-long videos such as egocentric recordings, live streams, or surveillance footage spanning days to weeks, remains a challenge. For

Bridging Sequence and Graph Structure for Epigenetic Age Prediction

arXiv:2605.10541v1 Announce Type: new Abstract: Epigenetic clocks based on DNA methylation have emerged as powerful tools for estimating biological age, with broad applications in aging research, age-

Bridging Spectral Operator Learning and U-Net Hierarchies: SpectraNet for Stable Autoregressive PDE Surrogates

arXiv:2605.09096v1 Announce Type: new Abstract: Neural operators for time-dependent PDEs face a structural tension: spectral architectures (FNO and descendants) inherit exponential rollout-error growt

Agents

Bridging the Cognitive Gap: A Unified Memory Paradigm for 6G Agentic AI-RAN

arXiv:2605.10036v1 Announce Type: cross Abstract: As 6G evolves, the radio access network must transcend traditional automation to embrace agentic AI capable of perception, reasoning, and evolution. A

agentsarxiv-cs-ai

BROS: Bias-Corrected Randomized Subspaces for Memory-Efficient Single-Loop Bilevel Optimization

arXiv:2605.10288v1 Announce Type: new Abstract: Stochastic bilevel optimization (SBO) has become a standard framework for hyperparameter learning, data reweighting, representation learning, and data-m

safetyarxiv-cs-lg

BubbleSpec: Turning Long-Tail Bubbles into Speculative Rollout Drafts for Synchronous Reinforcement Learning

arXiv:2605.08862v1 Announce Type: cross Abstract: Reinforcement Learning (RL) has become a cornerstone for improving the performance of Large Language Models (LLMs). However, its rollout phase constit

Budget-Efficient Automatic Algorithm Design via Code Graph

arXiv:2605.10598v1 Announce Type: new Abstract: Large language models (LLMs) have emerged as powerful tools for automatic algorithm design (AAD). However, existing pipelines remain inefficient. They o

Building Korean linguistic resource for NLU data generation of banking app CS dialog system

arXiv:2605.10241v1 Announce Type: new Abstract: Natural language understanding (NLU) is integral to task-oriented dialog systems, but demands a considerable amount of annotated training data to increa

researcharxiv-cs-cl

Built Environment Reasoning from Remote Sensing Imagery Using Large Vision--Language Models

arXiv:2605.08404v1 Announce Type: cross Abstract: This work investigates the use of large language models (LLMs) for tasks in smart cities. The core idea is to leverage remote sensing imagery to chara

bViT: Investigating Single-Block Recurrence in Vision Transformers for Image Recognition

arXiv:2605.10661v1 Announce Type: cross Abstract: Vision Transformers (ViTs) are built by stacking independently parameterized blocks, but it remains unclear how much of this depth requires layer spec

Byte-Exact Deduplication in Retrieval-Augmented Generation: A Three-Regime Empirical Analysis Across Public Benchmarks

model-releasesarxiv-cs-cl

arXiv:2605.09611v1 Announce Type: new Abstract: This preprint presents an empirical analysis of byte-exact chunk-level deduplication in Retrieval-Augmented Generation (RAG) pipelines. We measure conte

C-CoT: Counterfactual Chain-of-Thought with Vision-Language Models for Safe Autonomous Driving

model-releasesarxiv-cs-cv

arXiv:2605.10744v1 Announce Type: new Abstract: Safety-critical planning in complex environments, particularly at urban intersections, remains a fundamental challenge for autonomous driving. Existing

Local Ai

C2L-Net: A Data-Driven Model for State-of-Charge Estimation of Lithium-Ion Batteries During Discharge

arXiv:2605.08653v1 Announce Type: new Abstract: Accurate state-of-charge (SOC) estimation is critical for the safe and efficient operation of lithium-ion batteries in battery management systems (BMS).

local-aiarxiv-cs-ai

CachePrune: Teaching LLMs What Not to Follow via KV-Cache Editing

arXiv:2504.21228v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are susceptible to indirect prompt injection attacks, where the model inadvertently responds to instructions inje

CADBench: A Multimodal Benchmark for AI-Assisted CAD Program Generation

arXiv:2605.10873v1 Announce Type: cross Abstract: Recovering editable CAD programs from images or 3D observations is central to AI-assisted design, but progress is difficult to measure because existin

CAGS: Color-Adaptive Volumetric Video Streaming with Dynamic 3D Gaussian Splatting

arXiv:2605.09279v1 Announce Type: cross Abstract: Volumetric video (VV) streaming enables real-time, immersive access to remote 3D environments, powering telepresence, ecological monitoring, and robot

researcharxiv-cs-cv

CalBench: Evaluating Coordination-Privacy Trade-offs in Multi-Agent LLMs

arXiv:2605.09823v1 Announce Type: cross Abstract: We introduce CalBench, a controlled evaluation environment for studying multi-agent coordination through calendar scheduling. In CalBench, N agents ea

CalibFree: Self-Supervised View Feature Separation for Calibration-Free Multi-Camera Multi-Object Tracking

arXiv:2605.09245v1 Announce Type: new Abstract: Multi-camera multi-object tracking (MCMOT) faces significant challenges in maintaining consistent object identities across varying camera perspectives,

researcharxiv-cs-cv

Calibrate, Don't Curate: Label-Efficient Estimation from Noisy LLM Judges

arXiv:2605.09702v1 Announce Type: cross Abstract: Multi-judge evaluation is increasingly used to assess LLMs and reward models, and the prevailing heuristic is to curate: keep the most accurate judges

researcharxiv-cs-cl

CALYREX: Cross-Attention LaYeR EXtended Transformers for System Prompt Anchoring

arXiv:2605.09737v1 Announce Type: new Abstract: Modern large language models (LLMs) rely on system prompts to establish behavioral constraints and safety rules. Standard causal self-attention treats p

CAMAL: Improving Attention Alignment and Faithfulness with Segmentation Masks

arXiv:2605.08325v1 Announce Type: cross Abstract: Many vision datasets now provide segmentation masks in addition to annotated images to support a wide range of tasks. In this work, we propose Class A

Can Agent Benchmarks Support Their Scores? Evidence-Supported Bounds for Interactive-Agent Evaluation

arXiv:2605.10448v1 Announce Type: new Abstract: Interactive agent benchmarks map an agent run to a binary outcome through outcome checks. When these checks rely on surface level signals or fail to cap

Can Deep Research Agents Retrieve and Organize? Evaluating the Synthesis Gap with Expert Taxonomies

model-releasesarxiv-cs-cl

arXiv:2601.12369v3 Announce Type: replace Abstract: Deep Research Agents increasingly automate survey generation, yet whether they match human experts at retrieving essential papers and organizing the

Can Language Models Analyze Data? Evaluating Large Language Models for Question Answering over Datasets

arXiv:2605.10419v1 Announce Type: cross Abstract: This paper investigates the effectiveness of large language models (LLMs) in answering questions over datasets. We examine their performance in two sc

Can Language Models Identify Side Effects of Breast Cancer Radiation Treatments?

arXiv:2605.08439v1 Announce Type: new Abstract: Accurately communicating the side effects of cancer treatments to cancer survivors is critical, particularly in settings such as informed consent, where

researcharxiv-cs-cl

Can LLMs Estimate Student Struggles? Human-AI Difficulty Alignment with Proficiency Simulation for Item Difficulty Prediction

arXiv:2512.18880v2 Announce Type: replace-cross Abstract: Accurate estimation of item (question or task) difficulty is critical for educational assessment but suffers from the cold start problem. Whil