Search: “concepts”

arXiv:2604.01404v2 Announce Type: replace-cross Abstract: How do language models retrieve entity-specific facts from their parameters? We investigate this question by searching for sparse, entity-sele

arXiv:2605.17456v1 Announce Type: cross Abstract: Multiple instance learning (MIL) is the standard approach for whole-slide image (WSI) classification and survival prediction, where attention-based mo

For a quarter century, the Google search box has been one of the most recognizable interfaces in computing: a thin white rectangle, a blinking cursor, a few typed words, and a list of blue links. On T

arXiv:2605.18601v1 Announce Type: new Abstract: Modern interactive video world models have achieved impressive visual fidelity, yet lack fine-grained multi-entity control and cross-entity, cross-world

arXiv:2605.17990v1 Announce Type: new Abstract: We present a real-time gaze tracking system that directly acquires task-relevant latent features using a fully passive optical encoder. Instead of formi

arXiv:2605.17120v1 Announce Type: new Abstract: arly identification of motor impairment in infancy relies on expert visual assessment of spontaneous movement, motivating the development of automated,

arXiv:2402.15058v3 Announce Type: replace-cross Abstract: We combine standard persistent homology with image persistent homology to define a novel way of characterizing shapes and interactions between

arXiv:2605.18549v1 Announce Type: new Abstract: Large Reasoning Models (LRMs) introduce new opportunities for safety monitoring through their Chain of Thought (CoT) reasoning. However, CoT is not alwa

arXiv:2605.17340v1 Announce Type: new Abstract: Time series foundation models rely on large-scale pretraining over diverse datasets across domains, yet their heterogeneity in temporal patterns could h

arXiv:2602.20706v2 Announce Type: replace Abstract: This paper introduces online algorithms with unreliable guidance (OAG), a model for ML-augmented online decision-making that cleanly separates the p

arXiv:2601.09495v3 Announce Type: replace Abstract: With the emergence of massively parallel processing units, parallelization has become a desirable property for new sequence models. The ability to p

arXiv:2509.19590v2 Announce Type: replace Abstract: Evaluations of generative models are now ubiquitous, and their outcomes critically shape public and scientific expectations of AI's capabilities. Ye

arXiv:2605.18732v1 Announce Type: cross Abstract: While scaling laws govern aggregate large language model performance, no scaling law has linked factual recall to both model size and training-data co

arXiv:2605.18537v1 Announce Type: cross Abstract: This paper introduces the Manifold Probe, a supervised method for discovering representation manifolds in superposition. The method generalizes linear

arXiv:2605.18570v1 Announce Type: new Abstract: Cross-domain knowledge alignment is essential for integrating heterogeneous medical systems, yet existing approaches typically treat entity alignment as

arXiv:2605.17169v1 Announce Type: new Abstract: Agentic AI is rapidly proliferating across diverse real-world domains such as software engineering, yet public trust has not kept pace. The central reas

arXiv:2602.08169v2 Announce Type: replace-cross Abstract: Inference-time steering offers a promising way to control language models (LMs) without retraining. However, standard approaches typically rel

arXiv:2603.14462v2 Announce Type: replace-cross Abstract: Honey bee colony losses threaten global pollination services, yet current monitoring systems treat each hive as an isolated unit, ignoring the

arXiv:2602.12280v2 Announce Type: replace Abstract: Visual illusions traditionally rely on spatial manipulations such as multi-view consistency. In this work, we introduce Progressive Semantic Illusio

arXiv:2603.01092v2 Announce Type: replace Abstract: Scientific discovery is constrained not only by what is true, but by what is cognitively available to the researchers currently exploring a field. M

This post likely discusses how humor can be an effective vehicle for communicating truth or revealing reality in ways that straightforward statements cannot. Musk may be commenting on how comedic fram

arXiv:2605.16775v1 Announce Type: cross Abstract: Self-supervised learning (SSL) has advanced medical image analysis be enabling learning form large unlabelled data. However, in brain magnetic resonan

David Holz expresses a poetic interpretation of Blue Ocean Strategy, describing a vision of unprecedented market space and opportunity so vast it appears almost limitless—using the metaphor of an ocea

arXiv:2601.16398v2 Announce Type: replace-cross Abstract: Algorithmic audits are essential tools for examining systems for properties required by regulators or desired by operators. Current audits of

arXiv:2605.17173v1 Announce Type: cross Abstract: Large language models exhibit safety degradation in non-English languages. Standard evaluation relies on Jailbreak Success Rate (JSR), which confounds

arXiv:2605.16877v1 Announce Type: new Abstract: Zero-shot textual explanations aim to make image classifiers more transparent by probing their internal representations, without relying on task-specifi

arXiv:2605.15921v1 Announce Type: new Abstract: Object removal aims to eliminate specified objects from images while plausibly inpainting the affected regions with background content. Current training

arXiv:2512.08052v3 Announce Type: replace-cross Abstract: Embodied agents, such as robots and virtual characters, must continuously select actions to execute tasks effectively, solving complex sequent

arXiv:2605.15848v1 Announce Type: cross Abstract: Conversational interfaces powered by large language models (LLMs) are widely used for ideation and analysis, yet their linear structure limits explora

arXiv:2605.15942v1 Announce Type: cross Abstract: Open-vocabulary segmentation models often struggle to generalize to unseen combinations of object categories and attributes, because fine-grained desc

arXiv:2605.15456v1 Announce Type: cross Abstract: Solving imaging inverse problems has usually been addressed by designing proper prior models of the underlying signal. However, minimizing the data fi

arXiv:2508.18167v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in understanding and generating human-like text, yet they largely operate as

arXiv:2605.16164v1 Announce Type: new Abstract: Despite their ubiquity, variational autoencoders (VAEs) inherently suffer from posterior collapse, a failure mode in which latent variables are effectiv

arXiv:2605.15326v1 Announce Type: new Abstract: Reliable detection of humans beneath forest canopy remains a difficult remote-sensing challenge due to sparse, structured, and viewpoint-dependent occlu

arXiv:2510.02734v2 Announce Type: replace-cross Abstract: Deep learning, particularly with the advancement of Large Language Models, has transformed biomolecular modeling, with protein language models

arXiv:2507.17572v3 Announce Type: replace Abstract: Global optimization has gained attraction over the past decades, thanks to the development of both theoretical foundations and efficient numerical r

arXiv:2506.14829v2 Announce Type: replace-cross Abstract: AI for Social Impact (AI4SI) is an emergent field harnessing interdisciplinarities between the fields of artificial intelligence (AI), machine

This post likely discusses implementing non-intrusive feedback mechanisms in conversational AI systems that leverage familiar UI patterns to provide detailed user input without disrupting the natural

Often overlooked is the Frankfurt School’s central role, alongside French postmodernists, in forging Critical Theory and exporting it to America, where it evolved into one of the most influential (des

We're still celebrating the moms who build, Mother's Day or not. Ruth is a designer who spent years making digital products without ever learning to code. The moment Replit's AI agent landed in the ID

arXiv:2510.19973v4 Announce Type: replace-cross Abstract: The path to higher network autonomy in 6G lies beyond the mere optimization of key performance indicators (KPIs), requiring systems that perce

arXiv:2605.14169v1 Announce Type: new Abstract: Memory systems are critical for role-playing agents (RPAs) to maintain long-horizon consistency. However, existing RPA memory methods (e.g., profiling)

arXiv:2605.14569v1 Announce Type: new Abstract: Reconstructing dynamic visual experiences as videos from functional magnetic resonance imaging (fMRI) is pivotal for advancing the understanding of neur

arXiv:2509.20846v3 Announce Type: replace Abstract: Time series generation (TSG) synthesizes realistic sequences and has achieved remarkable success. Among TSG, conditional models generate sequences g

arXiv:2605.14988v1 Announce Type: new Abstract: Text-to-video diffusion models generate realistic videos, but often fail on prompts requiring fine-grained compositional understanding, such as relation

arXiv:2508.01916v3 Announce Type: replace-cross Abstract: Understanding internal representations of neural models is a core interest of mechanistic interpretability. Due to its large dimensionality, t