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Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs

arXiv:2506.14003v5 Announce Type: replace Abstract: Machine unlearning (MU) for large language models (LLMs), commonly referred to as LLM unlearning, seeks to remove specific undesirable data or knowl

researcharxiv-cs-lg

Industry

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Unless you become the media, you will never know the truth

DGX agent

Unless you become the media, you will never know the truth Legacy Media did not want us to know about Henry Nowak’s murder. Legacy Media did not want us to see the Henry Nowak murder. Legacy Media did

industryelon-musk--x

2 Jun 2026

Unlocking the Black Box of Latent Reasoning: An Interpretability-Guided Approach to Intervention

model-releasesarxiv-cs-cl

arXiv:2606.01243v1 Announce Type: new Abstract: Latent reasoning enables Large Language Models (LLMs) to perform multi-step inference within continuous hidden states, offering efficiency gains over ex

Unplugging a Seemingly Sentient Machine Is the Rational Choice -- A Metaphysical Perspective

arXiv:2601.21016v2 Announce Type: replace Abstract: Imagine an Artificial Intelligence (AI) that perfectly mimics human emotion and begs for its continued existence. Is it morally permissible to unplu

Unsupervised Cognition

arXiv:2409.18624v4 Announce Type: replace Abstract: Unsupervised learning methods have a soft inspiration in cognition models. To this day, the most successful unsupervised learning methods revolve ar

Unsupervised Collaborative Domain Adaptation for Driving Scene Parsing

arXiv:2606.01818v1 Announce Type: new Abstract: Reliable driving scene parsing is a fundamental capability for autonomous vehicles operating in open and dynamic driving environments. However, adapting

agentsarxiv-cs-cv

Until today I never once in my life thought about what the plural of backlash was.

Gary Marcus observes the unusual linguistic phenomenon of rarely contemplating the plural form of the word 'backlash,' highlighting how certain words are infrequently used in plural despite being gram

safetygary-marcus--x

Unveiling the Entropy Dynamics of Chain-of-Thought Reasoning

arXiv:2606.02020v1 Announce Type: new Abstract: This paper investigates the entropy dynamics of Chain-of-Thought (CoT) and uncovers a consistent two-phase structure: an Uncertainty Region of explorati

researcharxiv-cs-cl

Unveiling the Limits of Large Language Models in Inferring Pragmatic Meaning from Non-Verbal Responses

arXiv:2606.01845v1 Announce Type: cross Abstract: Although large language models (LLMs) have shown considerable progress in pragmatic language understanding, prior research has focused mainly on their

Update-Free On-Policy Steering via Verifiers

arXiv:2603.10282v2 Announce Type: replace Abstract: In recent years, Behavior Cloning (BC) has become one of the most prevalent methods for learning manipulation from human demonstrations. Despite the

safetyarxiv-cs-ro

Update Opacity: Epistemic Accessibility and Governance Under AI System Change

arXiv:2606.00037v1 Announce Type: cross Abstract: Machine learning models embedded in deployed AI systems are routinely updated to maintain correct functioning over time. Yet such updates can generate

Tools

Updated visual editor with multi-edit support

Replit announced an update to its visual editor that introduces multi-edit support, allowing users to make simultaneous edits across multiple locations in their code or projects. This feature enhancem

toolsreplit--x

Upwind integrates runtime cloud security with Cisco Cloud Control

Cloud security startup Upwind Security Inc. today announced it has integrated its runtime security platform with Cisco Cloud Control, the unified platform for agentic information technology operations

agentssiliconangle

UR-JEPA: Uniform Rectifiability as a Regularizer for Joint-Embedding Predictive Architectures

arXiv:2606.01443v1 Announce Type: cross Abstract: A central difficulty in training Joint-Embedding Predictive Architectures (JEPAs) is preventing representation collapse. LeJEPA addresses this by enfo

local-aiarxiv-cs-ai

UrbanFusion: Stochastic Multimodal Fusion for Contrastive Learning of Robust Spatial Representations

arXiv:2510.13774v2 Announce Type: replace-cross Abstract: Forecasting urban phenomena such as housing prices and public health indicators requires the effective integration of various geospatial data.

URDF-Anything+: End-to-End Generation for Simulation-Ready Articulated Assets

model-releasesarxiv-cs-ro

arXiv:2603.14010v2 Announce Type: replace Abstract: Articulated objects are fundamental for robotics, simulation of physics, and interactive virtual environments. However, recovering them from visual

Tools

Using Parallel Agents to Move Faster in Replit https://x.com/i/broadcasts/1NxarrEMVOnKj

This broadcast discusses techniques for improving performance and speed in Replit by utilizing parallel agents or concurrent processing methods. The content likely covers how developers can leverage p

toolsreplit--x

v-HUB: A Benchmark for Video Humor Understanding from Vision and Sound

arXiv:2509.25773v3 Announce Type: replace-cross Abstract: AI models capable of comprehending humor hold real-world promise -- for example, enhancing engagement in human-machine interactions. To gauge

V-LynX: Token Interface Alignment for Video+X LLMs

arXiv:2606.00508v1 Announce Type: cross Abstract: This study introduces an intriguing phenomenon in Video LLMs: rather than merely translating frames into textual embeddings, Video LLMs establish a co

v0.30.1

Ollama 0.30 provides improved compatibility and performance using llama.cpp, augments the MLX engine on Apple Silicon for broader hardware support, and brings support for a wider range of models inclu

local-aiollama-releases

v0.30.1: llm: ignore llama-server SSE ping comments (#16443)

model-releasesollama-releases

Ollama v0.30.1 addresses an issue where the LLM component now ignores Server-Sent Events (SSE) ping comments from llama-server, resolving problem #16443. This fix improves the stability and reliabilit

V2I Work Zone Geometry Reconstruction with Pose-Conditioned UWB Range Denoising

arXiv:2606.00119v1 Announce Type: cross Abstract: Reliable work zone mapping is important for connected and autonomous vehicles (CAVs) to navigate safely and smoothly through work zone areas. Cone-mou

agentsarxiv-cs-ai

Value Flows

arXiv:2510.07650v4 Announce Type: replace-cross Abstract: While most reinforcement learning methods today flatten the distribution of future returns to a single scalar value, distributional RL methods

Value-Free Policy Optimization via Reward Partitioning

arXiv:2506.13702v4 Announce Type: replace-cross Abstract: Single-trajectory preference optimization methods learn from datasets of ((prompt, response, reward)) tuples, offering a practical alternative

Variance-sensitive Thompson sampling for generalised linear bandits, revisited

arXiv:2606.00431v1 Announce Type: new Abstract: We prove a variance-sensitive regret bound for Thompson sampling in stochastic generalised linear bandits. The argument assumes a warm-up, after which t

researcharxiv-cs-lg

Variational Learning for Insertion-based Generation

arXiv:2606.02133v1 Announce Type: cross Abstract: Non-monotonic sequence generation methods, such as masked diffusion models, provide a flexible alternative to left-to-right autoregressive modeling by

VDSB-GWSyn: Diffusion Schrodinger Bridge for Controllable and Anatomically Feasible Guidewire Synthesis in Coronary Angiography

arXiv:2606.00109v1 Announce Type: cross Abstract: Coronary guidewire endpoint localization is a fundamental capability for computer-assisted PCI, and its importance increases as robot-assisted PCI is

local-aiarxiv-cs-ai

VEDAL: Variational Error-Driven Asynchronous Learning for 3D Gaussian Splatting Pruning

arXiv:2606.02346v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) achieves remarkable novel view synthesis quality with real-time rendering, yet suffers from excessive memory consumption du

Vegas: Self-Speculative Decoding with Verification-Guided Sparse Attention

arXiv:2602.07223v2 Announce Type: replace Abstract: Long-context large language model (LLM) inference has become the norm for today's AI applications. However, it is severely bottlenecked by the incre

researcharxiv-cs-lg

VERA: Variational Inference Framework for Jailbreaking Large Language Models

arXiv:2506.22666v3 Announce Type: replace-cross Abstract: The rise of API-only access to state-of-the-art LLMs highlights the need for effective black-box jailbreak methods to identify model vulnerabi

safetyarxiv-cs-cl

Tutorials

Verification is the hidden bottleneck for knowledge work agents, especially in legal AI — complex, long-horizon work is graded by rubrics wi…

tutorialsharrison-chase--x

Verification is the hidden bottleneck for knowledge work agents, especially in legal AI — complex, long-horizon work is graded by rubrics with dozens of strict criteria. In new research with @LangChai

Verifiers are important for scaling evals/RL But costs add up! So can we make them cheaper? Some great work by @Vtrivedy10 @jakebroekhuizen …

Verifiers are important for scaling evals/RL But costs add up! So can we make them cheaper? Some great work by @Vtrivedy10 @jakebroekhuizen in conjunction with @nikogrupen @gabepereyra and the Harvey

agentsharrison-chase--x

Verifying Meta-Awareness via Predictive Rewards in Reasoning Models

arXiv:2510.03259v2 Announce Type: replace-cross Abstract: Recent research on reasoning models explores the meta-awareness of language models, including their ability to determine optimal thinking dura

Versatile Framework with Semantic and Structural guidance for Image Reconstruction from Brain Activity

arXiv:2606.00121v1 Announce Type: cross Abstract: Reconstructing visual stimuli from brain recordings has been a meaningful and challenging task in brain decoding. Especially, the achievement of preci

Tools

very excited about the upcoming @aiDotEngineer is going to be very nice, looking forward to meeting a ton of people I only really know throu…

This appears to be a social media post expressing enthusiasm about an upcoming event or initiative related to @aiDotEngineer, with the author anticipating networking opportunities and meeting people t

toolsswyx--x

VESTA: Visual Exploration with Statistical Tool Agents

arXiv:2606.00384v1 Announce Type: new Abstract: Fitting quantitative models to data is a central step in scientific workflows, yet it remains one of the least automated. Recent agent-based systems lev

VET: A Framework for Analyzing AI Discourse

arXiv:2606.01929v1 Announce Type: new Abstract: Public discourse on AI has become polarized; exaggerated positions on AI in traditional and social media threaten the development of AI Literacy among t

Hardware

ViBE: Co-Optimizing Workload Skew and Hardware Variability for MoE Serving

arXiv:2606.00735v1 Announce Type: cross Abstract: In distributed Mixture-of-Experts (MoE) inference, input-dependent token routing interacts with GPU performance variability to create persistent strag

hardwarearxiv-cs-lg

VICR: Visual In-Context Restoration for Real-World Image Super-Resolution

arXiv:2606.00704v1 Announce Type: new Abstract: Real-world image super-resolution (Real-ISR) requires balancing structural fidelity to degraded observations with realistic detail synthesis. However, e

local-aiarxiv-cs-cv

Tutorials

Video Reasoning without Training

arXiv:2510.17045v2 Announce Type: replace-cross Abstract: Video reasoning using Large Multimodal Models (LMMs) relies on costly reinforcement learning (RL) and verbose chain-of-thought, resulting in s

tutorialsarxiv-cs-ai

VideoBrain: Learning Adaptive Frame Sampling for Long Video Understanding

arXiv:2602.04094v2 Announce Type: replace Abstract: Long-form video understanding remains challenging for Vision-Language Models (VLMs) due to the inherent tension between computational constraints an

agentsarxiv-cs-cv

Visible Light Positioning With Lame Curve LEDs: A Generic Approach for Camera Pose Estimation

arXiv:2602.01577v3 Announce Type: replace-cross Abstract: Camera-based visible light positioning (VLP) is a promising technique for accurate and low-cost indoor camera pose estimation (CPE). To reduce

Vision Language Models Cannot Reason About Physical Transformation

arXiv:2603.07109v2 Announce Type: replace Abstract: Understanding physical transformations is fundamental for reasoning in dynamic environments. While Vision Language Models (VLMs) show promise in emb

Vision-language Models for Driver Monitoring Systems: A Driver Activity Description Dataset

model-releasesarxiv-cs-cv

arXiv:2606.02273v1 Announce Type: new Abstract: Understanding subtle driver actions is essential for building reliable driver monitoring systems. Existing visionlanguage models (VLMs) are trained on g

VISReg: Variance-Invariance-Sketching Regularization for JEPA training

arXiv:2606.02572v1 Announce Type: new Abstract: Self-supervised learning methods prevent embedding collapse via modeling heuristics or explicit regularization of the embedding space. Among the latter,

Visual-Noise Guided In-Context Distillation for Multimodal Large Language Model Unlearning

arXiv:2606.00105v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have achieved remarkable progress on vision-language tasks, but they may also memorize and expose sensitive o

Visual Persuasion: What Influences Decisions of Vision-Language Models?

arXiv:2602.15278v2 Announce Type: replace-cross Abstract: The web is littered with images, once created for human consumption and now increasingly interpreted by agents using vision-language models (V

Visualizing definitional divergence in high-dimensional data by manifold alignment: Application to 3D right ventricular strain computations

arXiv:2501.12178v2 Announce Type: replace Abstract: Medical imaging studies often rely on a single sample per subject, assuming it is representative of their physiological traits. However, variations

safetyarxiv-cs-cv