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IRPol-Fuse: Energy-structure coordination for infrared polarization fusion under low visibility

arXiv:2608.07848v1 Announce Type: new Abstract: Robust perception under low-visibility conditions requires fused imagery that jointly preserves infrared thermal saliency and polarization-derived struc

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Is CLIP Cross-Eyed? Revealing and Mitigating Center Bias in the CLIP Family

DGX agent

arXiv:2604.05971v2 Announce Type: replace-cross Abstract: Recent research has shown that contrastive vision-language models such as CLIP often lack fine-grained understanding of visual content. While

safetyarxiv-cs-cl

11 Aug 2026

Is the ACL Responsible NLP Checklist a Box-Ticking Exercise? A Large-Scale Analysis of EMNLP 2025

model-releasesarxiv-cs-cl

arXiv:2608.09280v1 Announce Type: new Abstract: Responsible NLP practice includes a) transparency, b) ethics, and c) societal impacts. The Responsible NLP Checklist aims to push these goals, and promo

Jagle: Building a Large-Scale Japanese Multimodal Post-Training Dataset for Vision-Language Models

arXiv:2604.02048v2 Announce Type: replace Abstract: Developing vision-language models (VLMs) that generalize across diverse tasks requires large-scale training datasets with diverse content. In Englis

Jako Tako or Fluent? Presenting PoVisLE: A Polish Vision-Language Evaluation

model-releasesarxiv-cs-cl

arXiv:2608.07763v1 Announce Type: new Abstract: Vision-language models (VLMs) have achieved strong performance on tasks such as image captioning, visual question answering, and image-to-text generatio

JaleesBench: Are AI Assistants Good Spiritual Company?

arXiv:2608.07508v1 Announce Type: cross Abstract: Large language models are already advisors to millions of people of faith who bring them real decisions. The pressing question for a person of faith i

agentsarxiv-cs-ai

Janus: An Algorithm-Evaluator Co-Evolution Framework for LLM-Driven Discovery under Expensive Evaluation Budgets

arXiv:2608.08189v1 Announce Type: new Abstract: LLM-driven program discovery relies on rapid evaluator feedback, but many scientific and engineering tasks require high-fidelity simulations, hardware e

JEPA-WAM: Learning Vision-Language-Action Policies with Joint-Embedding World Modeling

arXiv:2608.09381v1 Announce Type: new Abstract: Robust robot control benefits from explicitly modeling state transitions, but video-generation world action models (WAMs) introduce substantial deployme

safetyarxiv-cs-ro

JSGS: JPEG State-Guided Supervision for 3D Gaussian Splatting from Mixed-Quality Views

arXiv:2608.08659v1 Announce Type: new Abstract: Standard 3D Gaussian Splatting (3DGS) assumes that every input image faithfully samples scene radiance. However, mixed-quality JPEG images violate this

JUMP-lite: Compact, reproducible benchmarking of cell representations

arXiv:2608.07632v1 Announce Type: cross Abstract: Image-based profiling captures rich phenotypic signatures for drug discovery and functional genomics. Large public datasets like JUMP Cell Painting no

JustLLMGRPO: Radiographic Control for Chest X-Ray Generation

arXiv:2608.08046v1 Announce Type: new Abstract: Text-conditioned chest X-ray generation aims to synthesize realistic radiographs that faithfully depict specified findings. Existing work has primarily

Keep It Simple: Multi-Key Episodic Memory Retrieval for Ultra-Long Video Understanding

arXiv:2608.07663v1 Announce Type: cross Abstract: When videos extend from hours to days, directly processing them end-to-end becomes impractical for current Multi-modal Large Language Models (MLLMs).

agentsarxiv-cs-ai

Kernel Methods for Refined Prophet Inequalities

arXiv:2608.08662v1 Announce Type: cross Abstract: The single-selection prophet inequality is a canonical Bayesian online selection problem in which independent nonnegative values arrive sequentially a

KGCache: Amortized Subgraph Retrieval for KG Reasoning with LLMs

arXiv:2608.07954v1 Announce Type: new Abstract: Large language models can answer knowledge-intensive questions more reliably when they are grounded with knowledge graphs, but systems such as Think-on-

KGCaRe: Explainable Complex Conditional Question Answering using Automatic Knowledge Graph Construction and Context Retrieval with LLMs

arXiv:2608.09779v1 Announce Type: cross Abstract: Answering complex conditional questions using Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) remains a challenge, particularly

Knowing When to Ask: Resolving Uncertainty in Human-Robot Joint Planning via Explicit Dialogue and Implicit Intent Cues

arXiv:2603.07822v2 Announce Type: replace Abstract: Effective human-robot collaboration in open-world environments requires joint planning under uncertainty about the task, the environment, and the hu

safetyarxiv-cs-ro

Knowing You Is Everything: LLM Agents Achieve Near-Perfect Profile-Consistent Reaction Prediction in Social Media Simulation

arXiv:2608.07498v1 Announce Type: cross Abstract: Autonomous AI agents in social media present concrete risks to democratic discourse and platform governance, while also offering tools for pre-deploym

Knowledge-Distilled End-to-End Reinforcement Learning for Smooth 6-DOF Thrust Control and Rapid Adaptation to Ocean Currents in Remotely Operated Vehicles

arXiv:2608.08598v1 Announce Type: new Abstract: With the continuous improvement of computational capabilities, end-to-end reinforcement learning has been rapidly developed for remotely operated vehicl

safetyarxiv-cs-ro

KumbhDoot: A Scale-Ready, LLM-Bounded Architecture for Mass-Gathering Public-Service Assistants

arXiv:2608.07520v1 Announce Type: cross Abstract: Mass religious gatherings such as the Kumbh Mela concentrate tens of millions of people into a single region over a few weeks, producing intense, repe

KVDiagnosis: A Diagnostic Benchmark for KV-Cache Compression in Long-Context Language Models

arXiv:2608.09412v1 Announce Type: new Abstract: KV-cache compression reduces long-context memory, but aggregate task scores reveal neither which correct executions fail nor why. We present KVDiagnosis

Label-Free Parkinson's Disease Screening from Face and Voice through Mechanistic Interpretability

arXiv:2608.08976v1 Announce Type: new Abstract: Parkinson's disease (PD) is the second most common neurodegenerative disorder. Typical machine learning screening methods require PD labels, but the ava

Local Ai

Label Granularity Skew in Federated Learning with Hierarchical Image Classification

arXiv:2608.09236v1 Announce Type: new Abstract: Federated learning enables privacy-preserving collaboration across distributed devices without centralizing local data. However, clients may differ not

local-aiarxiv-cs-lg

Tutorials

LAD-COD: Language-Aligned Dense Perception for Camouflaged Object Detection

arXiv:2608.07941v1 Announce Type: new Abstract: Camouflaged object detection (COD) aims to segment objects that exhibit high visual similarity to their surroundings, which reduces foreground-backgroun

tutorialsarxiv-cs-cv

Large Language Models Align with the Human Brain during Creative Thinking

arXiv:2604.03480v2 Announce Type: replace-cross Abstract: Creative thinking is a fundamental aspect of human cognition, and divergent thinking-the capacity to generate novel and varied ideas-is widely

Large Multimodal Agents for Intelligent Transportation Systems: Architectures, Evidence, and Deployment Challenges

arXiv:2608.08184v1 Announce Type: new Abstract: Large multimodal agents (LMAs) are increasingly proposed for intelligent transportation systems (ITS), but existing studies often conflate multimodality

LASA: Language-and-Source-Anchored Alignment for Domain Generalized Semantic Segmentation

arXiv:2608.08805v1 Announce Type: new Abstract: Domain Generalization Semantic Segmentation (DGSS) focuses on generalizing knowledge from labeled source domains to unseen target domains where data is

safetyarxiv-cs-cv

Latent-Frequency Validity: Fast Spectral Editing with Screened Video-VAE Transfer Operators

arXiv:2608.07569v1 Announce Type: cross Abstract: Direct spectral editing in video-VAE latents can control noise, flicker, smoothness, and frequency content without a decode--filter--reencode pass. Ho

Applications

Latent World Models with Monotone Planning Costs for Image-Goal Navigation

arXiv:2608.09073v1 Announce Type: new Abstract: Image-goal navigation with latent world models requires not only accurate future prediction, but also a planning cost that reliably ranks candidate acti

applicationsarxiv-cs-ro

LatticeMind: A Conflict-Aware Memory Primitive for Multi-Agent Systems

arXiv:2608.08236v1 Announce Type: new Abstract: Multi-agent LLM systems often fail not for lack of candidate answers, but because they have no persistent mechanism for deciding which incompatible clai

agentsarxiv-cs-ai

LAUDE: LLM-Assisted Unit Test Generation and Debugging of Hardware DEsigns

arXiv:2601.08856v3 Announce Type: replace-cross Abstract: Unit tests are critical in the hardware design lifecycle to ensure that component design modules are functionally correct and conform to the s

LAVE: Latent Visual Evidence-Enhanced Planning for Video Tool-use Agents

arXiv:2608.07585v1 Announce Type: new Abstract: Long-video understanding requires models to efficiently acquire and reuse sparse visual evidence from long and redundant video streams. Recent video too

agentsarxiv-cs-cv

Layerwise goal-oriented adaptivity for neural ODEs: an optimal control perspective

arXiv:2601.07397v2 Announce Type: replace-cross Abstract: In this work, we propose a novel layerwise adaptive construction method for neural network architectures. Our approach is based on a goal--ori

LazyHMC: Hamiltonian Monte Carlo Simulation for Lazy, Infinite Dimensional Probabilistic Programs

arXiv:2608.08588v1 Announce Type: cross Abstract: Hamiltonian Monte Carlo (HMC) is a successful generic inference method in probabilistic programming, but in its ordinary formulation it needs gradient

Learning aligned EEG representations with subject-specific encoders

arXiv:2606.16462v2 Announce Type: replace-cross Abstract: Cross-subject EEG decoding promises more training data, but it also exposes neural networks to strong inter-subject distribution shifts. We st

Learning an Interior Layout Policy in a Domain Specific Language Action Space

arXiv:2608.07547v1 Announce Type: cross Abstract: Indoor scene layout generation is a challenging task in interior design. Existing methods often oversimplify the task by reducing room conditions to c

Learning Deep Modality-Shared Self-Expressiveness for Image Clustering with Textual Information

arXiv:2608.08418v1 Announce Type: new Abstract: Leveraging textual information for image clustering has emerged as a promising direction, largely owing to the powerful representations learned by Visio

safetyarxiv-cs-cv

Learning from Consensus and Disagreement: Unsupervised On-Policy Self-Distillation with Minority-Trajectory Contrast

arXiv:2608.08764v1 Announce Type: cross Abstract: On-policy self-distillation improves language-model reasoning by querying a teacher on states actually visited by the student. Recent methods create a

Learning from Environmental Feedback: Credit Assignment across Multiple Timescales for Agentic Reinforcement Learning

arXiv:2608.08255v1 Announce Type: cross Abstract: Agentic reinforcement learning (RL) often suffers from delayed and sparse rewards in real-world environments. A promising solution to this challenge i

agentsarxiv-cs-cl

Learning How the World Evolves: Extrapolative Video World Models via Latent Dynamics Reasoning

arXiv:2608.09926v1 Announce Type: new Abstract: The world evolves following its dynamics, i.e., its laws of motion. However, leading video diffusion models largely fit the pixels without modeling how

Learning human joint torques from pixels

arXiv:2608.09083v1 Announce Type: new Abstract: Estimating human joint torques from visual observations is a key step toward bringing biomechanical analysis from controlled laboratories to real-world

Learning Multi-Timescale Interventions under Safety and Resource Constraints

arXiv:2508.03875v2 Announce Type: replace Abstract: Many sequential decision problems offer qualitatively different ways of influencing the environment: some interventions act immediately, whereas oth

safetyarxiv-cs-lg

Learning Physical Interaction: A Survey of Tactile- and Force-aware Robot Learning

arXiv:2608.07558v1 Announce Type: cross Abstract: Physically grounded robot intelligence requires robots to perceive, reason about, and regulate their interactions with the physical world. This capabi

Learning Preference Adaptation for Large Language Model Personalization via Verbal Reinforcement Learning

arXiv:2608.09507v1 Announce Type: cross Abstract: Natural language user preferences provide an interpretable interface for LLM personalization. However, universal preference summaries often contain in

Learning Structural Illumination for Unsupervised Low-light Enhancement

arXiv:2608.08153v1 Announce Type: new Abstract: Existing unsupervised low-light image enhancement (LLIE) methods often estimate illumination directly from the entire low-light input, without separatin

Learning to Coordinate Symbolic Tools: LLM Agents for Verified Sum-of-Squares Certificates

arXiv:2608.00326v2 Announce Type: replace Abstract: Tool calling allows large language models (LLMs) to invoke external computation during problem solving, a useful capability in various fields includ

Learning to Modulate, Not to Cycle: Soft Actor---Critic Recovers Inverter-Style Heat-Pump Control

arXiv:2608.09453v1 Announce Type: cross Abstract: On--off cycling is the main cause of compressor wear in residential heat pumps, yet reinforcement learning (RL) controllers for buildings typically op

Learning to Triage Vulnerability Reports from Program Analysis: An Empirical Study in Node.js

arXiv:2510.20739v2 Announce Type: replace-cross Abstract: Program analysis tools often produce large volumes of candidate vulnerability reports that require costly manual review, creating a practical

Learning under Opponent Unawareness in Linear-Quadratic Stochastic Games

arXiv:2608.08268v1 Announce Type: cross Abstract: As firms increasingly deploy machine learning for strategic decision-making, understanding algorithmic interactions has become central to operations r

agentsarxiv-cs-lg