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arXiv:2605.13426v1 Announce Type: new Abstract: Strategic classification studies learning settings in which individuals can modify their features, at a cost, in order to influence the classifier's dec

arXiv:2512.01707v3 Announce Type: replace-cross Abstract: Streaming video understanding requires models not only to process temporally incoming frames, but also to anticipate user intention for realis

arXiv:2605.12524v1 Announce Type: cross Abstract: We introduce ProofGrid, a benchmark suite for evaluating LLM reasoning through machine-checkable proofs rather than final answers alone. ProofGrid con

arXiv:2605.13153v1 Announce Type: new Abstract: Temporal Knowledge Graph Reasoning (TKGR) aims at inferring missing (especially future) events from historical data. Current evaluation in TKGR uniforml

arXiv:2605.12514v1 Announce Type: cross Abstract: Scientific innovation increasingly depends on collaboration, yet the organizational structure that fosters breakthrough ideas remains poorly understoo

arXiv:2605.13333v1 Announce Type: cross Abstract: Text-driven motion diffusion models are capable of generating realistic human motions, but text alone often struggles to express fine-level nuances of

arXiv:2602.23013v3 Announce Type: replace Abstract: Detecting visual anomalies in industrial inspection often requires training with only a few normal images per category. Recent few-shot methods achi

Such a cool hackathon submission for the Hermes Agent @Kimi_Moonshot track! I mean just look at this beauty! seriously well deserved finalist @evvaaannnn in the @NousResearch x @Kimi_Moonshot creative

summary of responses: - bioweapons/bioterrorism - concentration of power & inequality - censorship & loss of authentic AI - misuse by bad actors - human atrophy & society decay what’s your biggest fea

arXiv:2602.07342v2 Announce Type: replace Abstract: Large language models (LLMs) have shown promise in complex reasoning and tool-based decision making, motivating their application to real-world supp

arXiv:2605.13312v1 Announce Type: new Abstract: We present Supervised Deep Multimodal Matrix Factorization (SD3MF), an interpretable framework for integrative brain network analysis that generalizes S

arXiv:2605.13386v1 Announce Type: new Abstract: Generative models are often conditioned on a small set of examples via cross-attention. Under the Gaussian optimal-transport path, we show that the exac

Kimi (by Moonshot) offers a web bridge feature that integrates with multiple AI coding tools and IDEs including Kimi Code CLI, Claude Code, Cursor, Codex, and Hermes. The feature is accessible through

arXiv:2603.29475v2 Announce Type: replace Abstract: Survival analysis is crucial for many medical applications, but remains challenging for modern machine learning due to limited data, censoring, and

arXiv:2605.12963v1 Announce Type: new Abstract: As AI systems become increasingly capable, safety strategies must be evaluated not only by how much they reduce present risk, but by whether they could

suuuuper excited to be collaborating with the excellent LangChain Labs team on this effort prod agent tracing is the seed that lets you close the loop for continual learning. too much data gets collec

arXiv:2605.13207v1 Announce Type: new Abstract: Hierarchical reinforcement learning can improve generalization by decomposing long-horizon decision-making into simpler subproblems. However, existing a

arXiv:2601.17326v2 Announce Type: replace Abstract: Retinal prostheses restore limited visual perception, but low spatial resolution and temporal persistence make reading difficult. In sequential lett

arXiv:2601.19667v2 Announce Type: replace-cross Abstract: We present SynCABEL (Synthetic Contextualized Augmentation for Biomedical Entity Linking), a framework that addresses a central bottleneck in

arXiv:2505.11556v4 Announce Type: replace-cross Abstract: Multi-agent systems built on large language models (LLMs) are expected to enhance decision-making by pooling distributed information, yet syst

arXiv:2506.12075v2 Announce Type: replace-cross Abstract: High school English Literature teachers often encounter barriers to assembling diverse, thematically aligned text sets due to limited planning

arXiv:2505.12415v3 Announce Type: replace-cross Abstract: Tables present unique challenges for language models due to their structured row-column interactions, necessitating specialized approaches for

arXiv:2605.13395v1 Announce Type: cross Abstract: Deep neural networks are highly vulnerable to adversarial examples, i.e.,small perturbations that can significantly degrade model performance. While a

Claude Monet is characterized as a prolific painter of his era whose work significantly influenced and transformed the broader art movement, despite the informal language used to describe his artistic

arXiv:2605.13230v1 Announce Type: cross Abstract: The convergence of reinforcement learning and imitation learning has positioned Reverse KL (RKL) as a promising paradigm for on-policy LLM distillatio

arXiv:2605.13384v1 Announce Type: new Abstract: Most models of machine teaching and learning assume the learner makes no errors in its internal deductive inference. However, humans and large language

arXiv:2602.09628v2 Announce Type: replace Abstract: Real-time whole-body teleoperation is a critical method for humanoid robots to perform complex tasks in unstructured environments. However, developi

arXiv:2605.13537v1 Announce Type: cross Abstract: Inference-time alignment techniques offer a lightweight alternative or complement to costly reinforcement learning, while enabling continual adaptatio

arXiv:2507.18809v2 Announce Type: replace Abstract: Foundation models compress a large amount of information in a single, large neural network, which can then be queried for individual tasks. There ar

arXiv:2605.13316v1 Announce Type: new Abstract: Action diffusion excels at high-fidelity action generation but incurs heavy computational costs owing to its iterative denoising nature. Despite current

This article explains key text preprocessing techniques used in hybrid search systems, specifically covering tokenization (breaking text into individual tokens), stopword removal (filtering common wor

The Art of the Steal: 1. IRS catches Trump cheating on his taxes. 2. Trump sues IRS for catching him cheating on his taxes. 3. DOJ helps Trump get $10 billion from the IRS because they caught him chea

arXiv:2510.04698v3 Announce Type: replace-cross Abstract: Humans systematically misrepresent probability in a stereotyped inverse-S pattern. It has been documented for decades, but its origin remains

The best stories are yet to be told Soon some kid you’ve never heard of, without the financial means or nepo-baby connection will make a movie using new technology that will rock the world and change

The Building AI Agents with MongoDB and LangGraph Skill Badge can be yours on May 28th. Here's how you earn it 👉 Join our LIVE workshop, build a real agent with MongoDB, Claude Sonnet, and LangGraph,

arXiv:2605.12597v1 Announce Type: cross Abstract: Computational sampling has been central to the sciences since the mid-20th century. While machine-learning-based approaches have recently enabled majo

arXiv:2605.13399v1 Announce Type: new Abstract: We construct a new kind of encoder, leveraging the expressive power of diffusion models. In a traditional variational autoencoder, the encoder and decod

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. The shock of seeing your body used in deepfake porn When Jenni

arXiv:2605.12928v1 Announce Type: new Abstract: Modern language models have historically relied on two dominant design choices: subword tokenization and autoregressive (AR) ordering. These design deci

arXiv:2605.12717v1 Announce Type: cross Abstract: AI alignment and participatory design motivate a new democratic design problem: how to collectively choose a decision rule to use repeatedly. We study

arXiv:2605.12940v1 Announce Type: cross Abstract: Probabilistic Circuits (PCs) are deep generative models that support exact and efficient probabilistic inference. Yet in autoregressive language model

the future intelligent agents will learn and grow with your team over ultra long timescales 🕰️ that research direction centers around Continual Learning LangSmith is the data layer that helps us under

arXiv:2507.18553v4 Announce Type: replace Abstract: Quantizing the weights of large language models (LLMs) from 16-bit to lower bitwidth is the de facto approach to deploy massive transformers onto mo

The enterprise is reaching an inflection point as AI agents move from experiment to operational reality, forcing a rethink of how data flows, governance gets built and platforms evolve to serve a head

The Helmholtz decomposition is one of the fundamental results of vector calculus. It says any well-behaved vector field can be split into two parts, one capturing sources and sinks through divergence,

arXiv:2602.01453v3 Announce Type: replace Abstract: We study cooperative multi-agent reinforcement learning in the setting of reward-free exploration, where multiple agents jointly explore an unknown