Search: “concepts”

langchain is one of the few teams that actually explains the engineering behind agent concepts instead of just naming them. loop engineering, managed agents, memory systems. every time a new concept d

arXiv:2606.07034v1 Announce Type: new Abstract: AI-generated image detectors achieve high accuracy on in-distribution data but often fail on unseen generators. A key obstacle to understanding this fai

arXiv:2609.22174v1 Announce Type: new Abstract: Anticipating emerging research directions is a critical goal of AI-assisted science. Existing methods mainly predict which concepts will co-occur in fut

arXiv:2609.24554v1 Announce Type: new Abstract: Concepts are commonly defined as abstract, compact representations of knowledge and treated as basic units of intelligent behavior. Yet, cognition, psyc

arXiv:2608.28733v1 Announce Type: cross Abstract: Indoor 3D Scene Graphs (3DSGs) represent environments as multi-layer hierarchies that connect observed geometric primitives (e.g., planes) to higher-l

arXiv:2608.15698v1 Announce Type: new Abstract: Visual document retrieval is a critical component of multimodal retrieval-augmented generation, aiming to identify query-relevant pages from document co

arXiv:2606.23312v1 Announce Type: new Abstract: Operating in complex real-world environments requires robots to understand their surroundings on a functional semantic level. This demands a detailed mu

arXiv:2605.09591v1 Announce Type: new Abstract: Segmentation is a fundamental vision task underlying numerous downstream applications. Recent promptable segmentation models, such as Segment Anything M

arXiv:2605.01609v1 Announce Type: new Abstract: We test whether the causal inner product of itet{park2024linear} -- defined by the unembedding covariance Sigma -- enables cross-lingual concept transpo

arXiv:2609.34742v1 Announce Type: new Abstract: Recent studies suggest that large language models encode emotion concepts as structured internal representations, but most existing work focuses on text

arXiv:2503.10547v3 Announce Type: replace Abstract: Concept-based explanations help users understand vision models through recognizable visual patterns. However, existing methods often rely on correla

arXiv:2609.06020v1 Announce Type: new Abstract: Conservation increasingly relies on camera traps that collect more wildlife imagery than experts can manually analyze, making animal re-identification (

arXiv:2407.00966v3 Announce Type: replace Abstract: In traditional models of supervised learning, the goal of a learner-- given examples from an arbitrary joint distribution on R^d imes {pm 1}-- is to

arXiv:2608.10251v1 Announce Type: new Abstract: A transformer's answer lives on one axis: the direction its unembedding reads. Its intermediate states largely do not, and that off-axis position is usu

'You need a rich set of concepts in your mind to think creatively and fluently about how to move something forward.' It's never just one loop! A project is many, many loops with the agent. And the und

@LangChain always reveals the technical principles behind agent concepts, like loop engineering, managed agents and memories.👍 That's why I recommend LC docs to agent developers and users around me, t

arXiv:2603.09787v2 Announce Type: replace Abstract: Explainable artificial intelligence (XAI) aims to provide human-interpretable insights into the behavior of deep neural networks (DNNs), typically b

arXiv:2602.17605v2 Announce Type: replace-cross Abstract: In environmental monitoring, data collection is often costly, sparse, and shaped by urgent public-health needs. This is particularly true for

arXiv:2605.08837v1 Announce Type: cross Abstract: Abstract concepts - justice, theory, availability - have no single perceivable referent; in the human brain, their meaning emerges from a web of exper

arXiv:2604.07729v1 Announce Type: cross Abstract: Large language models (LLMs) sometimes appear to exhibit emotional reactions. We investigate why this is the case in Claude Sonnet 4.5 and explore imp

arXiv:2604.07886v1 Announce Type: new Abstract: We investigate how and to what extent hierarchical relations (e.g., Japan subset Eastern Asia subset Asia) are encoded in the internal representat

arXiv:2606.18328v2 Announce Type: replace Abstract: Intelligent robots should not only recover from failures, but also acquire the abstract knowledge needed to avoid them in the future. While reinforc

OpenAI’s tweet (posted Oct 7 2026 at 6:05 PM) promotes the idea that visual content can deepen comprehension of a topic, highlighting how images make concepts “come to life.” The post, part of OpenAI’

arXiv:2609.32671v1 Announce Type: cross Abstract: Cross-modal retrieval has been advanced by vision-language pre-trained models that encode images and texts into a shared dense embedding space. While

arXiv:2609.08879v1 Announce Type: new Abstract: Cancer segmentation models can fail silently, generating plausible but incorrect masks that risk missed findings or unnecessary biopsies. A critical que

arXiv:2608.25347v1 Announce Type: new Abstract: The Jacobian lens (J-lens) has been proposed as a way to read verbalizable representations from language models. However, its principle and meaning lack

Recommended agent skill. /eli5 works great for visualizing deep technical concepts! I find it speeds up my thought process and helps me collaborate better with agents. Try /eli5 with Pi and Ox Alpha i

A lot of the questions we get from developers are about the concepts behind the API: TTFT, context windows, sampling, fine-tuning, quantization, deployment tradeoffs. We added Learn to the Together do

arXiv:2607.24425v1 Announce Type: new Abstract: Large language models place structured concepts on geometrically faithful manifolds: weekdays lie on a circle, months on another, usually taken to be a

This Google AI post likely promotes a tool or platform for exploring creative ideas, scaling visual concepts, and beginning creative projects, with a shortened URL linking to more details. The post ap

arXiv:2606.28643v1 Announce Type: new Abstract: The widespread adoption of generative AI models has intensified concerns about misuse, including the creation of unsafe or disturbing imagery. To mitiga

arXiv:2606.16196v2 Announce Type: replace-cross Abstract: Deep neural networks have achieved remarkable performance across medical imaging tasks, yet their tendency to overgeneralize under distributio

two things ready to share from this weekend: 📖 http://learn.activegraph.ai interactive site teaching activegraph concepts blog: https://activegraph.ai/blog/introducing-learn 💻 AG coder (open source) r

arXiv:2606.04118v1 Announce Type: new Abstract: This article situates large language models (LLMs) within the longer history of computational approaches to concept analysis in the history, philosophy,

arXiv:2603.29123v2 Announce Type: replace Abstract: The next-token prediction (NTP) objective trains language models to predict a single token at each step, even though many continuations can express

This post by Harrison Chase emphasizes the importance of mastering fundamental business and career concepts that may seem unglamorous but are critical for long-term success and risk mitigation. The co

arXiv:2605.10180v1 Announce Type: new Abstract: The rise of text-to-image (T2I) models has increasingly raised concerns regarding the generation of risky content, such as sexual, violent, and copyrigh

arXiv:2510.08638v3 Announce Type: replace-cross Abstract: DINOv2 is routinely deployed to recognize objects, scenes, and actions; yet the nature of what it perceives remains unknown. As a working base

The new DeepSeek-V4, like DeepSeek-V3, uses concepts from our 2024 paper on Self-Rewarding LMs -- see screenshots of their tech reports! (Congrats!) Classical :) Self-Rewarding LMs from Jan 2024: http

arXiv:2604.19775v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed as autonomous agents capable of reasoning, planning, and acting within interactive environments.

arXiv:2610.08303v1 Announce Type: new Abstract: Current evaluation of multilingual Large Language Models (LLMs) rests on an implicit Translation-Isomorphism Assumption (TIA): that semantic structures

arXiv:2608.22930v1 Announce Type: new Abstract: Agentic AI is a fascinating new tool for software development. It is a huge step forward compared to 'conventional' AI assisted coding, which in turn wa

arXiv:2608.16924v1 Announce Type: cross Abstract: This work-in-progress (WIP) innovative practice category paper presents LLM Odyssey, an open source, browser-based serious gaming platform comprising

arXiv:2608.15323v1 Announce Type: new Abstract: Understanding a model and its learning mechanisms in depth requires identifying when its internal structures become useful, rather than simply looking a

arXiv:2608.11367v1 Announce Type: cross Abstract: Estimating human gaze targets from images in-the-wild is an important and formidable task. Existing approaches primarily employ brittle, multi-stage p

arXiv:2608.04030v1 Announce Type: cross Abstract: Generative artificial intelligence (AI) has transformed text-to-image synthesis, yet its ability to represent specialized engineering domains remains