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Claude Code spend had gotten to $10.95M runrate peak at SemiAnalysis But then Opus 4.7 saved me. More token effecient for tasks, smarter, and no fast mode. Thank you @AnthropicAI You saved me from ban

Claude users can access more apps with Anthropic's AI now thanks to new connectors for everything from hiking to grocery shopping. Anthropic already supported connecting numerous work-related apps to

arXiv:2603.25383v3 Announce Type: replace Abstract: CLIP aligns image and text embeddings via contrastive learning and demonstrates strong zero-shot generalization. Its large-scale architecture requir

arXiv:2509.03740v3 Announce Type: replace-cross Abstract: Vision-language models (VLMs) like CLIP have shown impressive zero-shot and few-shot learning capabilities across diverse applications. Howeve

arXiv:2604.20824v1 Announce Type: new Abstract: The central problem in biomedical imaging are batch effects: systematic technical variations unrelated to the biological signal of interest. These batch

Cloud agent infrastructure has a lot of moving parts: VM isolation, session persistence, environment provisioning, orchestration, integrations. Each one is its own engineering challenge. In this post,

Natalie Breymeyer / Axios: Cloudsmith, which is building a cloud-native system to manage software artifacts, raised a 72M Series C, following a 23M Series B in 2025 — Cloudsmith, a platform that prote

arXiv:2604.19826v1 Announce Type: cross Abstract: AI coding assistants increasingly generate code alongside tests. How developers structure test code, whether inline with the implementation or in sepa

arXiv:2604.19772v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in scientific writing but struggle with book-length tasks, often producing inconsistent structure a

arXiv:2510.18471v2 Announce Type: replace-cross Abstract: While Large Language Models (LLMs) excel at code generation by learning from vast code corpora, a fundamental semantic gap remains between the

Codex settings refers to configuration options and parameters available for OpenAI's Codex model, a machine learning system trained to understand and generate code. This documentation likely covers ho

arXiv:2604.19750v1 Announce Type: cross Abstract: Recent advances in Large Language Model (LLM)-based agents have shown remarkable progress in code generation. However, current agent methods mainly re

arXiv:2604.19771v1 Announce Type: cross Abstract: LLM agents lack persistent memory, causing conversations to reset each session and preventing personalization over time. We present Lyzr Cognis, a uni

arXiv:2604.20027v1 Announce Type: cross Abstract: For state-of-the-art image understanding, Vision Transformers (ViTs) have become the standard architecture but their processing diverges substantially

arXiv:2508.00414v3 Announce Type: replace Abstract: General AI Agents are increasingly recognized as foundational frameworks for the next generation of artificial intelligence, enabling complex reason

arXiv:2604.20370v1 Announce Type: new Abstract: Forecasting the life-cycle trajectory of a newly launched product is important for launch planning, resource allocation, and early risk assessment. This

arXiv:2602.10386v2 Announce Type: replace Abstract: Graph problems are fundamentally challenging for large language models (LLMs). While LLMs excel at processing unstructured text, graph tasks require

arXiv:2510.10417v2 Announce Type: replace-cross Abstract: Gait recognition is an important biometric for human identification at a distance, particularly under low-resolution or unconstrained environm

LangChain, an open-source framework for developing applications with large language models, is recruiting new team members as shared by co-founder Harrison Chase on X (Twitter). The careers page invit

come work with us 🚀 everyone here is rlly nice, smart, curious, ships like crazy, and we make great Slack stickers I work with some world class people @LangChain! We're hiring for all sorts of roles -

Harrison Chase, co-founder and CEO of LangChain, appeared in a startup spotlight interview with Stephanie Wong. The discussion likely covered LangChain's development, its applications in AI and langua

arXiv:2604.19921v1 Announce Type: new Abstract: Negation is a common and important semantic feature in natural language, yet Large Language Models (LLMs) struggle when negation is involved in natural

arXiv:2604.20720v1 Announce Type: cross Abstract: Large language models (LLMs) often exhibit performance disparities across languages, with naive multilingual fine-tuning frequently degrading performa

arXiv:2602.12036v2 Announce Type: replace Abstract: Large-scale verifiable prompts underpin the success of Reinforcement Learning with Verifiable Rewards (RLVR), but they contain many uninformative ex

arXiv:2602.07473v2 Announce Type: replace Abstract: Partially observable Markov decision processes (POMDPs) are a fundamental model for sequential decision-making under uncertainty. However, many veri

arXiv:2604.20082v1 Announce Type: new Abstract: The trust in the predictions of Graph Neural Networks is limited by their opaque reasoning process. Prior methods have tried to explain graph networks v

arXiv:2604.20358v1 Announce Type: new Abstract: The Composed Image Retrieval (CIR) task provides a flexible retrieval paradigm via a reference image and modification text, but it heavily relies on exp

arXiv:2603.24725v2 Announce Type: replace Abstract: Recently, 3D Gaussian Splatting (3DGS) greatly accelerated mesh extraction from posed images due to its explicit representation and fast software ra

Confidently wrong is worse than just wrong. When an AI searches one giant knowledge base for everything, it finds something—and serves it up like it's the answer. That's not a model problem. That's a

Jerry Liu congratulated the ET30 Class of 2026 for ringing the Nasdaq closing bell, celebrating what appears to be an achievement by members of an executive or entrepreneurial cohort. The ET30 is like

A developer describes building a persistent-state AI system using Ollama with three models (a 4B router model, a 9B primary model, and a 9B 'subconscious' model) running on dual RTX 3060 GPUs, demonst

arXiv:2604.20241v1 Announce Type: new Abstract: Battery research is a rapidly growing and highly interdisciplinary field, making it increasingly difficult to track relevant expertise and identify pote

arXiv:2506.19977v2 Announce Type: replace Abstract: Understanding which parts of the retrieved context contribute to a large language model's generated answer is essential for building interpretable a

arXiv:2604.20021v1 Announce Type: cross Abstract: As Large Language Models (LLMs) become increasingly popular, caching responses so that they can be reused by users with semantically similar queries h

arXiv:2512.05070v2 Announce Type: replace-cross Abstract: Simulating the conditioned dynamics of diffusion processes, given their initial and terminal states, is an important but challenging problem i

arXiv:2604.20817v1 Announce Type: cross Abstract: Language models trained on natural text learn to represent numbers using periodic features with dominant periods at T=2, 5, 10. In this paper, we iden

Cool paper on diversity collapse in AI agents. It's a common issue with all the deployed multi-agent systems. New paper shows that multi-agent LLM systems converge on near-identical outputs over time,

arXiv:2604.20658v1 Announce Type: new Abstract: Multi-agent systems built from teams of large language models (LLMs) are increasingly deployed for collaborative scientific reasoning and problem-solvin

Copperhelm Inc., a startup building agentic artificial intelligence for cloud cybersecurity, today announced its launch with $7 million in seed funding led by TLV Partners. ToDay Ventures, ICON and Sa

arXiv:2603.23694v2 Announce Type: replace Abstract: Medical image registration is a fundamental task in medical image analysis, enabling the alignment of images from different modalities or time point

arXiv:2604.20246v1 Announce Type: cross Abstract: Industrial robotic manipulation demands reliable long-horizon execution across embodiments, tasks, and changing object distributions. While Vision-Lan

arXiv:2604.20172v1 Announce Type: new Abstract: Consider betting against a sequence of data in [0,1], where one is allowed to make any bet that is fair if the data have a conditional mean m_0 in (0,1)

arXiv:2604.20763v1 Announce Type: cross Abstract: Retrieval quality is the primary bottleneck for accuracy and robustness in retrieval-augmented generation (RAG). Current evaluation relies on heuristi

arXiv:2604.19941v1 Announce Type: new Abstract: Reliable crack detection and segmentation are vital for structural health monitoring, yet the scarcity of well-annotated data constitutes a major challe

arXiv:2505.14984v2 Announce Type: replace Abstract: Open-Domain Table Question Answering (TQA) involves retrieving relevant tables from a large corpus to answer natural language queries. Traditional d

arXiv:2604.19926v1 Announce Type: new Abstract: Large language models can generate plausible game code, but turning this capability into iterative creative improvement remains difficult. In practice,