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tl;dr - let's not just remove negative behavior from models, but also add positive ones 👍

tl;dr - let's not just remove negative behavior from models, but also add positive ones 👍 If anyone builds it, everyone thrives. Over the past decade, a lot of important work on AI alignment has focus

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TodyComm: Task-Oriented Dynamic Communication for Multi-Round LLM-based Multi-Agent System

DGX agent

arXiv:2602.03688v2 Announce Type: replace Abstract: Multi-round LLM-based multi-agent systems rely on effective communication structures to support collaboration across rounds. However, most existing

safetyarxiv-cs-ai

12 May 2026

Top-H Decoding: Adapting the Creativity and Coherence with Bounded Entropy in Text Generation

arXiv:2509.02510v2 Announce Type: replace-cross Abstract: Large language models (LLMs), despite their impressive performance across a wide range of tasks, often struggle to balance two competing objec

Towards Autonomous Railway Operations: A Semi-Hierarchical Deep Reinforcement Learning Approach to the Vehicle Rescheduling Problem

arXiv:2605.10257v1 Announce Type: new Abstract: Managing disruptions in railway traffic management is a major challenge. Rising traffic density and infrastructure limits increase complexity, making th

Towards Backdoor-Based Ownership Verification for Vision-Language-Action Models

arXiv:2605.09005v1 Announce Type: cross Abstract: Vision-Language-Action models (VLAs) support generalist robotic control by enabling end-to-end decision policies directly from multi-modal inputs. As

Towards Generative Predictive Display for Vision-Based Teleoperation: A Zero-Shot Benchmark of Off-the-Shelf Video Models

model-releasesarxiv-cs-cv

arXiv:2605.09670v1 Announce Type: cross Abstract: Teleoperation systems are fundamentally limited by communication latency, which degrades situational awareness and control performance. Predictive dis

Towards Shutdownable Agents: Generalizing Stochastic Choice in RL Agents and LLMs

arXiv:2604.17502v2 Announce Type: replace Abstract: Misaligned artificial agents might resist shutdown. One proposed solution is to train agents to lack preferences between different-length trajectori

TRAM: Training Approximate Multiplier Structures for Low-Power AI Accelerators

arXiv:2605.08231v1 Announce Type: cross Abstract: Reducing power consumption in AI accelerators is increasingly important. Approximate computing can reduce power consumption while keeping the accuracy

Transformers Can Implement Preconditioned Richardson Iteration for In-Context Gaussian Kernel Regression

arXiv:2605.08475v1 Announce Type: cross Abstract: Mechanistic accounts of in-context learning (ICL) have identified iterative algorithms for linear regression and related linear prediction tasks, ofte

UAV-Assisted Scan-to-Simulation for Landslides Using Physics-Informed Gaussian Splatting

arXiv:2605.10715v1 Announce Type: new Abstract: Landslide monitoring and simulation play an important role in urban safety assessment and disaster prevention. Existing landslide simulation pipelines t

safetyarxiv-cs-cv

Uncertainty-Aware and Decoder-Aligned Learning for Video Summarization

arXiv:2605.09507v1 Announce Type: new Abstract: Video summarization aims to produce a compact representation of a long video by selecting a subset of temporally important segments that best reflect hu

safetyarxiv-cs-cv

Unified Modeling of Lane and Lane Topology for Driving Scene Reasoning

model-releasesarxiv-cs-cv

arXiv:2605.08911v1 Announce Type: new Abstract: Autonomous vehicles need to perceive not only physical elements in the driving scene, such as lane lines and traffic lights, but also logical elements l

Upholding Epistemic Agency: A Brouwerian Assertibility Constraint for Responsible AI

arXiv:2603.03971v2 Announce Type: replace-cross Abstract: Generative AI can convert uncertainty into hypersuasive, authoritative-seeming verdicts, displacing the justificatory work on which democratic

safetyarxiv-cs-ai

VAE with Hyperspherical Coordinates: Improving Anomaly Detection from Hypervolume-Compressed Latent Space

arXiv:2601.18823v3 Announce Type: replace Abstract: Variational autoencoders (VAE) encode data into lower-dimensional latent vectors before decoding those vectors back to data. Once trained, one can h

applicationsarxiv-cs-lg

Value-Decomposed Reinforcement Learning Framework for Taxiway Routing with Hierarchical Conflict-Aware Observations

arXiv:2605.08754v1 Announce Type: new Abstract: Taxiway routing and on-surface conflict avoidance are coupled safety-critical decision problems in airport surface operations. Existing planning and opt

safetyarxiv-cs-ai

ViSRA: A Video-based Spatial Reasoning Agent for Multi-modal Large Language Models

arXiv:2605.10106v1 Announce Type: cross Abstract: Recent advances in Multi-modal Large Language Models (MLLMs) target 3D spatial intelligence, yet the progress has been largely driven by post-training

VISTA: A Benchmark for Real-Time Video Streaming under Network Impairments in Surgical Teleoperation

model-releasesarxiv-cs-ro

arXiv:2605.08886v1 Announce Type: cross Abstract: Real-time video streaming is crucial in surgical teleoperation, yet reproducible evaluation under realistic network impairments remains limited. This

Visual Hand Gesture Recognition with Deep Learning: A Comprehensive Review of Methods, Datasets, Challenges and Future Research Directions

arXiv:2507.04465v4 Announce Type: replace Abstract: The rapid evolution of deep learning (DL) models and the ever-increasing size of available datasets have raised the interest of the research communi

researcharxiv-cs-cv

VT-Bench: A Unified Benchmark for Visual-Tabular Multi-Modal Learning

arXiv:2605.08146v1 Announce Type: cross Abstract: Multi-model learning has attracted great attention in visual-text tasks. However, visual-tabular data, which plays a pivotal role in high-stakes domai

Weakly Supervised Concept Learning for Object-centric Visual Reasoning

arXiv:2605.08201v1 Announce Type: cross Abstract: Neurosymbolic systems promise to combine deep neural network's (DNN) processing of raw sensor inputs with few-shot performance of symbolic artificial

applicationsarxiv-cs-ai

What Software Engineering Looks Like to AI Agents? -- An Empirical Study of AI-Only Technical Discourse on MoltBook

arXiv:2605.08380v1 Announce Type: cross Abstract: AI agents are increasingly framed as software-engineering teammates, yet most research studies them inside human-centered workflows. Little is known a

When (and How) to Trust the Expert: Diagnosing Query-Time Expert-Guided Reinforcement Learning

arXiv:2605.09109v1 Announce Type: new Abstract: Many continuous-control problems ship with a competent but suboptimal controller (a tuned PID, a hand-designed gait). A growing family of methods uses s

When Child Inherits: Modeling and Exploiting Subagent Spawn in Multi-Agent Networks

arXiv:2605.08460v1 Announce Type: cross Abstract: Since the official release of ChatGPT in 2022, large language models (LLMs) have rapidly evolved from chatbot-style interfaces into agentic systems th

When Efficient Communication Explains Convexity

arXiv:2602.02821v2 Announce Type: replace Abstract: Much recent work has argued that the variation in the languages of the world can be explained from the perspective of efficient communication; in pa

researcharxiv-cs-cl

Tutorials

When Large Vision-Language Models Meet Person Re-Identification

arXiv:2411.18111v2 Announce Type: replace Abstract: Large Vision-Language Models (LVLMs) that incorporate visual models and large language models have achieved impressive results across cross-modal un

tutorialsarxiv-cs-cv

Why Low-Resource NLP Needs More Than Cross-Lingual Transfer: Lessons Learned from Luxembourgish

arXiv:2605.10714v1 Announce Type: cross Abstract: Cross-lingual transfer has become a central paradigm for extending natural language processing (NLP) technologies to low-resource languages. By levera

Willful Disobedience: Automatically Detecting Failures in Agentic Traces

arXiv:2603.23806v2 Announce Type: replace-cross Abstract: AI agents are increasingly embedded in real software systems, where they execute multi-step workflows through multi-turn dialogue, tool invoca

XTinyU-Net: Training-Free U-Net Scaling via Initialization-Time Sensitivity

arXiv:2605.09639v1 Announce Type: cross Abstract: While U-Net architectures remain the gold standard for medical image segmentation, their deployment in resource-constrained environments demands aggre

researcharxiv-cs-cv

A Cost-Effective and Climate-Resilient Air Pressure System for Rain Effect Reduction on Automated Vehicle Cameras

arXiv:2602.17472v2 Announce Type: replace Abstract: Recent advances in automated vehicles have focused on improving perception performance under adverse weather conditions; however, research on physic

researcharxiv-cs-ro

A Reproducible Multi-Architecture Baseline for Token-Level Chinese Metaphor Identification under the MIPVU Framework

model-releasesarxiv-cs-cl

arXiv:2605.07170v1 Announce Type: new Abstract: Metaphor is pervasive in everyday language, yet token-level computational identification of metaphor-related words in Chinese under the MIPVU framework

A Self-Healing Framework for Reliable LLM-Based Autonomous Agents

arXiv:2605.06737v1 Announce Type: cross Abstract: Autonomous agents based on Large Language Models (LLMs) are increasingly being utilized in complex software systems. However, reliability remains a si

A Wasserstein GAN-based climate scenario generator for risk management and insurance: the case of soil subsidence

arXiv:2605.06678v1 Announce Type: new Abstract: According to the United Nations Office for Disaster Risk Reduction (2025), the average annual cost of natural catastrophes increased from 70--80 billion

researcharxiv-cs-lg

Tutorials

Active teacher selection for reward learning

arXiv:2310.15288v3 Announce Type: replace Abstract: Reward learning techniques enable machine learning systems to learn objectives from human feedback. A core limitation of these systems is their assu

tutorialsarxiv-cs-ai

AdaTKG: Adaptive Memory for Temporal Knowledge Graph Reasoning

arXiv:2605.07121v1 Announce Type: new Abstract: Temporal knowledge graphs (TKGs) represent time-stamped relational facts and support a wide range of reasoning tasks over evolving events. However, exis

Advancing Reliable Synthetic Video Detection: Insights from the SAFE Challenge

arXiv:2605.06912v1 Announce Type: new Abstract: The proliferation of generative video technologies has intensified the need for reliable methods to detect and characterize synthetic media. To address

researcharxiv-cs-cv

Aggregation in conformal e-classification

arXiv:2605.07963v1 Announce Type: new Abstract: Aggregating conformal predictors is a standard way of balancing their predictive and computational efficiency while retaining their validity, at least a

researcharxiv-cs-lg

AGWM: Affordance-Grounded World Models for Environments with Compositional Prerequisites

arXiv:2605.06841v1 Announce Type: new Abstract: In model-based learning, the agent learns behaviors by simulating trajectories based on world model predictions. Standard world models typically learn a

AirBender: Adaptive Transportation of Bendable Objects Using Dual UAVs

arXiv:2605.07003v1 Announce Type: new Abstract: The interaction of robots with bendable objects in midair presents significant challenges in control, often resulting in performance degradation and pot

researcharxiv-cs-ro

Amortized Multi-Objective Optimization Across Tasks with Generative Solution Modeling

model-releasesarxiv-cs-lg

arXiv:2511.09598v5 Announce Type: replace Abstract: Many real-world applications require solving families of expensive multi-objective optimization problems~(EMOPs) under varying operational condition

Amortized-Precision Quantization for Early-Exit Vision Transformers

arXiv:2605.07317v1 Announce Type: cross Abstract: Vision Transformers (ViTs) achieve strong performance across vision tasks, yet their deployment with low-precision early exiting remains fragile. Exis

Local Ai

An Aerial Manipulator for Perception-Driven Flower Targeting Toward Contactless Pollination in Vertical Farming

arXiv:2605.06759v1 Announce Type: new Abstract: The decline of natural pollinators has created a major challenge for crop production in controlled indoor agriculture, particularly in vertical farming

local-aiarxiv-cs-ro

Anatomy of Unlearning: The Dual Impact of Fact Salience and Model Fine-Tuning

model-releasesarxiv-cs-cl

arXiv:2602.19612v3 Announce Type: replace Abstract: Machine Unlearning (MU) enables Large Language Models (LLMs) to remove unsafe or outdated information. However, existing work assumes that all facts

Attribution-Based Neuron Utility for Plasticity Restoration in Deep Networks

model-releasesarxiv-cs-lg

arXiv:2605.06834v1 Announce Type: new Abstract: Continual learning research attempts to conserve two fundamental capabilities: new knowledge acquisition and the preservation of previously acquired kno

AudioFace: Language-Assisted Speech-Driven Facial Animation with Multimodal Language Models

arXiv:2605.07478v1 Announce Type: new Abstract: Speech-driven facial animation requires accurate correspondence between acoustic signals and facial motion, especially for articulation-related mouth mo

applicationsarxiv-cs-cv

Beyond 'I cannot fulfill this request': Alleviating Rigid Rejection in LLMs via Label Enhancement

arXiv:2605.07883v1 Announce Type: new Abstract: Large Language Models (LLMs) rely on safety alignment to obey safe requests while refusing harmful ones. However, traditional refusal mechanisms often l

safetyarxiv-cs-cl

Beyond Linear Attention: Softmax Transformers Implement In-Context Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2605.07333v1 Announce Type: new Abstract: In-context reinforcement learning (ICRL) studies agents that, after pretraining, adapt to new tasks by conditioning on additional context without parame

Beyond Retrieval: A Multitask Benchmark and Model for Code Search

arXiv:2605.04615v2 Announce Type: replace-cross Abstract: Code search has usually been evaluated as first-stage retrieval, even though production systems rely on broader pipelines with reranking and d

Beyond Single Ground Truth: Reference Monism as Epistemic Injustice in ASR Evaluation

arXiv:2605.07084v1 Announce Type: new Abstract: Automatic speech recognition (ASR) evaluation compares system output to ground truth transcripts, with Word Error Rate (WER) quantifying the distance be

applicationsarxiv-cs-cl