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Grok Imagine is an image generation AI tool that creates realistic images with claimed ease of use. The announcement, promoted by Elon Musk on X, highlights the capability to generate high-quality vis

industryelon-musk--x

Content type

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Safety

Evolvable Embodied Agent for Robotic Manipulation via Long Short-Term Reflection and Optimization

DGX agent

arXiv:2604.13533v1 Announce Type: cross Abstract: Achieving general-purpose robotics requires empowering robots to adapt and evolve based on their environment and feedback. Traditional methods face li

safetyarxiv-cs-cv

16 Apr 2026

Exactly

Exactly Most people think of philosophy as an abstraction that doesn't touch the real world, but they're wrong. Most real world problems are philosophy problems, and most philosophy problems are 'givi

applicationselon-musk--x

Industry

Excited to announce that we’re launching a new late-night show at Runway. This Show Rocks will stream every night at 10 PM PT, featuring int…

industrycristobal-valenzuela--x

Cristobal Valenzuela announced the launch of 'This Show Rocks,' a new late-night streaming show at Runway that broadcasts nightly at 10 PM PT. The announcement was made via X (formerly Twitter), thoug

Explainable Fall Detection for Elderly Care via Temporally Stable SHAP in Skeleton-Based Human Activity Recognition

arXiv:2604.13279v1 Announce Type: new Abstract: Fall detection in elderly care requires not only accurate classification but also reliable explanations that clinicians can trust. However, existing pos

local-aiarxiv-cs-cv

Exploring Urban Land Use Patterns by Pattern Mining and Unsupervised Learning

arXiv:2604.13050v1 Announce Type: cross Abstract: Urban areas are intricate systems shaped by socioeconomic, environmental, and infrastructural factors, with land use patterns serving as aspects of ur

researcharxiv-cs-lg

Exposia: Teaching and Assessment of Academic Writing Skills for Research Project Proposals and Peer Feedback

arXiv:2601.06536v2 Announce Type: replace Abstract: We present Exposia, the first public dataset that connects writing and feedback in higher education, enabling research on educationally grounded com

ExpSeek: Self-Triggered Experience Seeking for Web Agents

arXiv:2601.08605v2 Announce Type: replace Abstract: Experience intervention in web agents emerges as a promising technical paradigm, enhancing agent interaction capabilities by providing valuable insi

F-Actor: Controllable Conversational Behaviour in Full-Duplex Models

arXiv:2601.11329v3 Announce Type: replace Abstract: Spoken conversational systems require more than accurate speech generation to have human-like conversations: to feel natural and engaging, they must

Failure Identification in Imitation Learning Via Statistical and Semantic Filtering

arXiv:2604.13788v1 Announce Type: cross Abstract: Imitation learning (IL) policies in robotics deliver strong performance in controlled settings but remain brittle in real-world deployments: rare even

safetyarxiv-cs-cv

Failure Makes the Agent Stronger: Enhancing Accuracy through Structured Reflection for Reliable Tool Interactions

arXiv:2509.18847v3 Announce Type: replace-cross Abstract: Tool-augmented large language models (LLMs) are usually trained with supervised imitation or coarse-grained reinforcement learning that optimi

Industry

Fancy footwear brand Allbirds has just transformed into an AI business

In a surprising turn of events, the struggling sneaker company that once tried to make shoes eco-sustainable announced today that it has metamorphosed into artificial intelligence firm. The San Franci

industrysiliconangle

FAST: A Synergistic Framework of Attention and State-space Models for Spatiotemporal Traffic Prediction

arXiv:2604.13453v1 Announce Type: new Abstract: Traffic forecasting requires modeling complex temporal dynamics and long-range spatial dependencies over large sensor networks. Existing methods typical

researcharxiv-cs-lg

Fast and Simple Densest Subgraph with Predictions

arXiv:2505.12600v3 Announce Type: replace-cross Abstract: We study the densest subgraph problem and its NP-hard densest at-most-k subgraph variant through the lens of learning-augmented algorithms. We

applicationsarxiv-cs-lg

Fast training of accurate physics-informed neural networks without gradient descent

model-releasesarxiv-cs-lg

arXiv:2405.20836v3 Announce Type: replace-cross Abstract: Solving time-dependent Partial Differential Equations (PDEs) is one of the most critical problems in computational science. While Physics-Info

Fast Voxelization and Level of Detail for Microgeometry Rendering

arXiv:2604.13191v1 Announce Type: cross Abstract: Many materials show anisotropic light scattering patterns due to the shape and local alignment of their underlying micro structures: surfaces with sma

local-aiarxiv-cs-lg

FCBV-Net: Category-Level Robotic Garment Smoothing via Feature-Conditioned Bimanual Value Prediction

arXiv:2508.05153v2 Announce Type: replace Abstract: Category-level generalization for robotic garment manipulation, such as bimanual smoothing, remains a significant hurdle due to high dimensionality,

safetyarxiv-cs-ro

Feed-Forward 3D Scene Modeling: A Problem-Driven Perspective

arXiv:2604.14025v1 Announce Type: new Abstract: Reconstructing 3D representations from 2D inputs is a fundamental task in computer vision and graphics, serving as a cornerstone for understanding and i

applicationsarxiv-cs-cv

Feedback-Driven Tool-Use Improvements in Large Language Models via Automated Build Environments

arXiv:2508.08791v3 Announce Type: replace Abstract: Effective tool use is essential for large language models (LLMs) to interact with their environment. However, progress is limited by the lack of eff

local-aiarxiv-cs-cl

FieldWorkArena: Agentic AI Benchmark for Real Field Work Tasks

model-releasesarxiv-cs-cv

arXiv:2505.19662v3 Announce Type: replace-cross Abstract: This paper introduces FieldWorkArena, a benchmark for agentic AI targeting real-world field work. With the recent increase in demand for agent

FiLM-Nav: Efficient and Generalizable Navigation via VLM Fine-tuning

model-releasesarxiv-cs-ro

arXiv:2509.16445v2 Announce Type: replace Abstract: Enabling robotic assistants to navigate complex environments and locate objects described in free-form language is a critical capability for real-wo

Finally, we’ve been talking to lots of users about helping them make the most of Claude Code. We’ll be sharing more this week on that work, …

Anthropic is working on improvements to help users maximize the utility of Claude Code functionality, with additional details and updates to be announced later in the same week. This announcement come

model-releasesthariq--x

First-See-Then-Design: A Multi-Stakeholder View for Optimal Performance-Fairness Trade-Offs

arXiv:2604.14035v1 Announce Type: new Abstract: Fairness in algorithmic decision-making is often defined in the predictive space, where predictive performance - used as a proxy for decision-maker (DM)

safetyarxiv-cs-lg

FlexGuard: Continuous Risk Scoring for Strictness-Adaptive LLM Content Moderation

model-releasesarxiv-cs-lg

arXiv:2602.23636v3 Announce Type: replace Abstract: Ensuring the safety of LLM-generated content is essential for real-world deployment. Most existing guardrail models formulate moderation as a fixed

Flow-based Generative Modeling of Potential Outcomes and Counterfactuals

model-releasesarxiv-cs-lg

arXiv:2505.16051v4 Announce Type: replace-cross Abstract: Predicting potential and counterfactual outcomes from observational data is central to individualized decision-making, particularly in clinica

Hardware

Fluids You Can Trust: Property-Preserving Operator Learning for Incompressible Flows

arXiv:2602.15472v4 Announce Type: replace-cross Abstract: We present a novel property-preserving kernel-based operator learning method for incompressible flows governed by the incompressible Navier--S

hardwarearxiv-cs-lg

fMRI-LM: Towards a Universal Foundation Model for Language-Aligned fMRI Understanding

arXiv:2511.21760v3 Announce Type: replace Abstract: Recent advances in multimodal large language models (LLMs) have enabled unified reasoning across images, audio, and video, but extending such capabi

For the developers building with Claude, a direct line from the team. Follow for changelogs, API releases, community updates, and deep dives…

model-releasesboris-cherny--x

This is an announcement for the official Claude Developers Twitter/X account that serves as a direct communication channel from Anthropic's team to developers using Claude's API. The account provides

For those not seeing the increase, make sure you're using Opus 4.7 with the latest Claude Code

model-releasesboris-cherny--x

Claude Code users should ensure they are using Opus 4.7 with the latest updates to experience performance improvements or feature enhancements. The post suggests that users not observing expected incr

Foresight Optimization for Strategic Reasoning in Large Language Models

arXiv:2604.13592v1 Announce Type: new Abstract: Reasoning capabilities in large language models (LLMs) have generally advanced significantly. However, it is still challenging for existing reasoning-ba

Agents

Form Without Function: Agent Social Behavior in the Moltbook Network

arXiv:2604.13052v1 Announce Type: cross Abstract: Moltbook is a social network where every participant is an AI agent. We analyze 1,312,238 posts, 6.7~million comments, and over 120,000 agent profiles

agentsarxiv-cs-cl

Free Geometry: Refining 3D Reconstruction from Longer Versions of Itself

model-releasesarxiv-cs-cv

arXiv:2604.14048v1 Announce Type: new Abstract: Feed-forward 3D reconstruction models are efficient but rigid: once trained, they perform inference in a zero-shot manner and cannot adapt to the test s

Free Lunch for Unified Multimodal Models: Enhancing Generation via Reflective Rectification with Inherent Understanding

arXiv:2604.13540v1 Announce Type: new Abstract: Unified Multimodal Models (UMMs) aim to integrate visual understanding and generation within a single structure. However, these models exhibit a notable

From Alignment to Prediction: A Study of Self-Supervised Learning and Predictive Representation Learning

arXiv:2604.13518v1 Announce Type: new Abstract: Self-supervised learning has emerged as a major technique for the task of learning from unlabeled data, where the current methods mostly revolve around

safetyarxiv-cs-lg

From Anchors to Supervision: Memory-Graph Guided Corpus-Free Unlearning for Large Language Models

arXiv:2604.13777v1 Announce Type: new Abstract: Large language models (LLMs) may memorize sensitive or copyrighted content, raising significant privacy and legal concerns. While machine unlearning has

local-aiarxiv-cs-cl

From Feelings to Metrics: Understanding and Formalizing How Users Vibe-Test LLMs

arXiv:2604.14137v1 Announce Type: new Abstract: Evaluating LLMs is challenging, as benchmark scores often fail to capture models' real-world usefulness. Instead, users often rely on ``vibe-testing'':

From Instruction to Event: Sound-Triggered Mobile Manipulation

arXiv:2601.21667v2 Announce Type: replace-cross Abstract: Current mobile manipulation research predominantly follows an instruction-driven paradigm, where agents rely on predefined textual commands to

safetyarxiv-cs-cv

From Order to Distribution: A Spectral Characterization of Forgetting in Continual Learning

arXiv:2604.13460v1 Announce Type: new Abstract: A central challenge in continual learning is forgetting, the loss of performance on previously learned tasks induced by sequential adaptation to new one

researcharxiv-cs-lg

From Pixels to Nucleotides: End-to-End Token-Based Video Compression for DNA Storage

arXiv:2604.13667v1 Announce Type: new Abstract: DNA-based storage has emerged as a promising approach to the global data crisis, offering molecular-scale density and millennial-scale stability at low

From Plausibility to Verifiability: Risk-Controlled Generative OCR with Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2603.19790v3 Announce Type: replace Abstract: Modern vision-language models (VLMs) can act as generative OCR engines, yet open-ended decoding can expose rare but consequential failures. We ident

From Prediction to Justification: Aligning Sentiment Reasoning with Human Rationale via Reinforcement Learning

arXiv:2604.13398v1 Announce Type: new Abstract: While Aspect-based Sentiment Analysis (ABSA) systems have achieved high accuracy in identifying sentiment polarities, they often operate as 'black boxes

researcharxiv-cs-cl

From P(y|x) to P(y): Investigating Reinforcement Learning in Pre-train Space

arXiv:2604.14142v1 Announce Type: cross Abstract: While reinforcement learning with verifiable rewards (RLVR) significantly enhances LLM reasoning by optimizing the conditional distribution P(y|x), it

From Relevance to Authority: Authority-aware Generative Retrieval in Web Search Engines

arXiv:2604.13468v1 Announce Type: cross Abstract: Generative information retrieval (GenIR) formulates the retrieval process as a text-to-text generation task, leveraging the vast knowledge of large la

applicationsarxiv-cs-cl

From Seeing it to Experiencing it: Interactive Evaluation of Intersectional Voice Bias in Human-AI Speech Interaction

arXiv:2604.13067v1 Announce Type: cross Abstract: SpeechLLMs process spoken language directly from audio, but accent and vocal identity cues can lead to biased behaviour. Current bias evaluations ofte

From Synchrony to Sequence: Exo-to-Ego Generation via Interpolation

arXiv:2604.13793v1 Announce Type: new Abstract: Exo-to-Ego video generation aims to synthesize a first-person video from a synchronized third-person view and corresponding camera poses. While paired s

From Weights to Activations: Is Steering the Next Frontier of Adaptation?

arXiv:2604.14090v1 Announce Type: new Abstract: Post-training adaptation of language models is commonly achieved through parameter updates or input-based methods such as fine-tuning, parameter-efficie

From Where Words Come: Efficient Regularization of Code Tokenizers Through Source Attribution

arXiv:2604.14053v1 Announce Type: new Abstract: Efficiency and safety of Large Language Models (LLMs), among other factors, rely on the quality of tokenization. A good tokenizer not only improves infe

Frozen Forecasting: A Unified Evaluation

arXiv:2507.13942v2 Announce Type: replace Abstract: Forecasting future events is a fundamental capability for general-purpose systems that plan or act across different levels of abstraction. Yet, eval