Search: “papers”

arXiv:2604.19399v1 Announce Type: new Abstract: Federated learning (FL) is a key paradigm for distributed model learning across decentralized data sources. Communication in each FL round typically con

arXiv:2604.18893v1 Announce Type: cross Abstract: A series of high-profile tragedies involving companion chatbots has triggered an unusually rapid regulatory response. Several jurisdictions, including

arXiv:2604.19528v1 Announce Type: cross Abstract: This technical note revisits the relationship between RaBitQ and TurboQuant under a unified comparison framework. We compare the two methods in terms

arXiv:2604.19593v1 Announce Type: cross Abstract: The importance of clear and correct text in legal documents cannot be understated, and, consequently, a grammatical error correction tool meant to ass

Source: https://news.mit.edu/2026/new-type-electrically-driven-artificial-muscle-fiber-0409?utm_source=robotnews.therundown.ai&utm_medium=newsletter&utm_campaign=unitree-s-cheapest-humanoid-goes-globa

This thread discusses how advances in AI tooling and accessible models have lowered barriers to entry for startups, enabling small teams to leverage capabilities previously requiring specialized ML ex

arXiv:2505.20779v5 Announce Type: replace Abstract: A hallmark of human innovation is recombination -- the creation of novel ideas by integrating elements from existing concepts and mechanisms. In thi

arXiv:2604.18236v1 Announce Type: new Abstract: In the context of robot learning for manipulation, curated datasets are an important resource for advancing the state of the art; however, available dat

arXiv:2506.01732v2 Announce Type: replace Abstract: Large Language Models (LLMs) are pre-trained on large data from different sources and domains. These datasets often contain trillions of tokens, inc

arXiv:2603.04592v3 Announce Type: replace Abstract: Standard Large Language Models (LLMs) are predominantly designed for static inference with pre-defined inputs, which limits their applicability in d

I tested @huggingface ml-intern, given the prompt 'Fine-tune a Segment Anything Model (SAM) on a useful medical dataset. Train the model, and provide a comprehensive tutorial in a Jupyter Notebook fil

arXiv:2604.17484v1 Announce Type: cross Abstract: Retrieving mathematical knowledge is a central task in both human-driven research, such as determining whether a result already exists, finding relate

arXiv:2511.21686v2 Announce Type: replace Abstract: Synthetic data has become increasingly important for training large language models, especially when real data is scarce, expensive, or privacy-sens

arXiv:2503.21248v3 Announce Type: replace Abstract: Large language models (LLMs) have shown potential in assisting scientific research, yet their ability to discover high-quality research hypotheses r

arXiv:2604.16821v1 Announce Type: new Abstract: Reach and Frequency (R&F) contract advertising is an important form of widely used brand advertising. Unlike performance advertising, R&F contracts emph

arXiv:2604.17141v1 Announce Type: new Abstract: The rapid growth of scientific literature calls for automated methods to assess and predict research impact. Prior work has largely focused on citation-

arXiv:2604.17143v1 Announce Type: new Abstract: Despite their substantial successes, AI agents continue to face fundamental challenges in terms of trustworthiness. Consider deep research agents, taske

arXiv:2604.17656v1 Announce Type: cross Abstract: Video-to-music (V2M) is the fundamental task of creating background music for an input video. Recent V2M models achieve audiovisual alignment by typic

arXiv:2510.17795v3 Announce Type: replace Abstract: Replicating AI research is a crucial yet challenging task for large language model (LLM) agents. Existing approaches often struggle to generate exec

arXiv:2604.15327v1 Announce Type: cross Abstract: Universities are microcosms of urban ecosystems, with concentrated consumption patterns in food, transport, energy, and product usage. These environme

arXiv:2604.15589v1 Announce Type: cross Abstract: Existing research on large language models (LLMs) for automated code compliance has primarily focused on performance, treating the models as black box

arXiv:2604.16042v1 Announce Type: cross Abstract: While Large Language Models (LLMs) have achieved strong performance across many NLP tasks, their opaque internal mechanisms hinder trustworthiness and

We are happy to share early results from Logos, our novel first-principles augmented intelligence system, that has enabled insightful results across domains. We start with series of results in physics

Localmaxxing.com is a platform in private testing phase with plans for public release the same week this announcement was made, designed to simplify benchmark sharing by eliminating the need for users

I am not convinced that we should be comfortable calling 'problem solving' or 'judgement' or whatever as skills that are impossible for AI to do well. Like any other skill, there are humans who are re

We only have spotty information about this very important topic. It suggests AI can be good at diagnosis, but the real world doesn't always match the experiments. https://x.com/emollick/status/1980474

WildChat is an amazing project. The project page seems not to be updated anymore, so people might not know that the dataset has been updated with a very large number of transcripts through July 2025:

One of the premier journals in my field... I think there are very valid reasons to set rules on AI in peer review (including disclosure), but the idea that all AI models steal your data is very 2023.

This post references a non-exhaustive collection of academics working on a particular topic, with Ethan Mollick directing readers to his previous tweets for additional examples and research. The speci

arXiv:2604.14161v1 Announce Type: new Abstract: Reliable evaluation is essential in machine learning research, yet methodological flaws-particularly data leakage-continue to undermine the validity of

arXiv:2602.22839v2 Announce Type: replace Abstract: Presentation generation requires deep content research, coherent visual design, and iterative refinement based on observation. However, existing pre

arXiv:2604.15216v1 Announce Type: cross Abstract: Mobility in urban and interurban areas, mainly by cars, is a day-to-day activity of many people. However, some of its main drawbacks are traffic jams

arXiv:2602.20370v2 Announce Type: replace Abstract: The universal approximation theorem establishes that neural networks can approximate any continuous function on a compact set. Later works in approx

arXiv:2604.14261v1 Announce Type: new Abstract: The rapid rise in AI conference submissions has driven increasing exploration of large language models (LLMs) for peer review support. However, LLM-base

Agent evals are drifting away from production reality. Most benchmarks use clean tasks, well-specified requirements, deterministic metrics, and retrospective curation. Production work is messier, with

arXiv:2604.13079v1 Announce Type: cross Abstract: Current AI alignment paradigms rely on behavioral correction: external supervisors (e.g., RLHF) observe outputs, judge against preferences, and adjust

arXiv:2604.13472v1 Announce Type: new Abstract: Cooperative multi-agent reinforcement learning (MARL) is widely used to address large joint observation and action spaces by decomposing a centralized c

arXiv:2504.21751v4 Announce Type: replace-cross Abstract: Modern software development demands code that is maintainable, testable, and scalable by organizing the implementation into modular components

arXiv:2604.13882v1 Announce Type: new Abstract: The evaluation of supervised machine learning models is a critical stage in the development of reliable predictive systems. Despite the widespread avail

arXiv:2509.25549v2 Announce Type: replace Abstract: Choroidal nevi are common benign pigmented lesions in the eye, with a small risk of transforming into melanoma. Early detection is critical to impro

Ethan Mollick reported that requesting Claude Opus 4.7 to write sestinas—a complex poetic form with strict structural requirements—frequently triggers the model's safety guardrails, suggesting the AI

Its noticeable how much of the whole practice of working with AI - the prompts, the skill files, the connectors, retrieval work, the markdown files, etc. - is a substitute for the real problem of cont

Just launched some great new providers in Stripe Projects (http://projects.dev): @huggingface @Cloudflare @OpenRouter @firecrawl @flydotio @Amplitude_HQ @mixpanel @inngest Many more coming later this

arXiv:2601.15170v2 Announce Type: replace Abstract: The rapid expansion of research across machine learning, vision, and language has produced a volume of publications that is increasingly difficult t

NEW Research from Google. Integration test failures are painful because the signal is buried in messy logs. Massive output, heterogeneous systems, low signal-to-noise ratio, and unclear root causes. T

arXiv:2604.13759v1 Announce Type: cross Abstract: Large language model (LLM) agents on multi-step tasks suffer reasoning degradation, looping, drift, stuck states, at rates up to 30% on hard tasks. Cu