Search: “research”

This has in fact (at various levels) happened more than 1000 times. Check out @DamienCharlotin’s tracker and my substack essays about it.

applicationsgary-marcus--x

This has in fact (at various levels) happened more than 1000 times. Check out @DamienCharlotin’s tracker and my substack essays about it. And it begins Sullivan & Cromwell just admitted to a federal j

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This is why I won't use proprietary hosted embedding models myself - I am more than happy to pay for a hosted solution (cheaper, faster and …

DGX agent

This is why I won't use proprietary hosted embedding models myself - I am more than happy to pay for a hosted solution (cheaper, faster and more convenient than self-hosting) but I want an open weight

toolssimon-willison--x

22 Apr 2026

this looks like a website but it’s an interactive generative video 🫨

this looks like a website but it’s an interactive generative video 🫨 Imagine every pixel on your screen, streamed live directly from a model. No HTML, no layout engine, no code. Just exactly what you

agentsyohei-nakajima--x

Time Series Augmented Generation for Financial Applications

model-releasesarxiv-cs-ai

arXiv:2604.19633v1 Announce Type: new Abstract: Evaluating the reasoning capabilities of Large Language Models (LLMs) for complex, quantitative financial tasks is a critical and unsolved challenge. St

Towards Optimal Agentic Architectures for Offensive Security Tasks

model-releasesarxiv-cs-ai

arXiv:2604.18718v1 Announce Type: cross Abstract: Agentic security systems increasingly audit live targets with tool-using LLMs, but prior systems fix a single coordination topology, leaving unclear w

Towards Reliable Human Evaluations in Gesture Generation: Insights from a Community-Driven State-of-the-Art Benchmark

arXiv:2511.01233v3 Announce Type: replace Abstract: We review human evaluation practices in automatic, speech-driven 3D gesture generation and find a lack of standardisation and frequent use of flawed

Tstars-Tryon 1.0: Robust and Realistic Virtual Try-On for Diverse Fashion Items

arXiv:2604.19748v1 Announce Type: new Abstract: Recent advances in image generation and editing have opened new opportunities for virtual try-on. However, existing methods still struggle to meet compl

Vibe coders are not going to like this. UC San Diego just published the first real field study of experienced developers using AI agents. Th…

Vibe coders are not going to like this. UC San Diego just published the first real field study of experienced developers using AI agents. They watched 13 of them code in the wild and surveyed 99 more.

agentsgary-marcus--x

Visual Adversarial Attack on Vision-Language Models for Autonomous Driving

arXiv:2411.18275v2 Announce Type: replace Abstract: Vision-language models (VLMs) have significantly advanced autonomous driving (AD) by enhancing reasoning capabilities. However, these models remain

safetyarxiv-cs-cv

Warmth and Competence in the Swarm: Designing Effective Human-Robot Teams

arXiv:2604.19270v1 Announce Type: new Abstract: As groups of robots increasingly collaborate with humans, understanding how humans perceive them is critical for designing effective human-robot teams.

agentsarxiv-cs-ro

We are excited to launch VideoGameBench on Antim Labs, created by @a1zhang, Thomas L. Griffiths (@cocosci_lab), @karthik_r_n, and @OfirPress…

VideoGameBench is a new benchmark launched on Antim Labs, created by a1zhang, Thomas L. Griffiths, Karthik R. N, and Ofir Press. The benchmark likely evaluates AI model performance on video game-relat

agentsyohei-nakajima--x

What’s new in the Agentic Data Cloud: Powering the System of Action

model-releasesgoogle-cloud-ai

Companies are shifting from gen AI that simply answers questions to autonomous agents that perceive, reason, and act on their behalf. Attempting to scale these agents on legacy stacks exposes structur

What’s next in Google AI infrastructure: Scaling for the agentic era

model-releasesgoogle-cloud-ai

AI is evolving from answering questions to reasoning and taking action. Companies who want to lead in today’s agentic era require computing infrastructure designed and optimized for these new requirem

Advancing MAPF Toward the Real World: A Scalable Multi-Agent Realistic Testbed (SMART)

arXiv:2503.04798v3 Announce Type: replace Abstract: We present Scalable Multi-Agent Realistic Testbed (SMART), a realistic and efficient software tool for evaluating Multi-Agent Path Finding (MAPF) al

agentsarxiv-cs-ro

Industry

AI Insider: 'Adding a Human Makes Your Team Worse' Emad Mostaque | @EMostaque TIMESTAMPS : 00:00 The models too dangerous to release 10:06 W…

AI Insider: 'Adding a Human Makes Your Team Worse' Emad Mostaque | @EMostaque TIMESTAMPS : 00:00 The models too dangerous to release 10:06 Why physics needs axioms — and AI doesn't 11:43 The MIND fram

industryemad-mostaque--x

AIM 2025 Rip Current Segmentation (RipSeg) Challenge Report

arXiv:2508.13401v3 Announce Type: replace Abstract: This report presents an overview of the AIM 2025 RipSeg Challenge, a competition designed to advance techniques for automatic rip current segmentati

Aligning Backchannel and Dialogue Context Representations via Contrastive LLM Fine-Tuning

arXiv:2604.16622v1 Announce Type: new Abstract: Backchannels (e.g., `yeah', `mhm', and `right') are short, non-interruptive feedback signals whose lexical form and prosody jointly convey pragmatic mea

AlphaContext: An Evolutionary Tree-based Psychometric Context Generator for Creativity Assessment

arXiv:2604.18398v1 Announce Type: new Abstract: Creativity has become a core competence in the era of LLMs and human-AI collaboration, underpinning innovation in real-world problem solving. Crucially,

applicationsarxiv-cs-cl

Annotation-Assisted Learning of Treatment Policies From Multimodal Electronic Health Records

arXiv:2507.20993v3 Announce Type: replace Abstract: We study how to learn treatment policies from multimodal electronic health records (EHRs) that consist of tabular data and clinical text. These poli

Anthropic gets $5B investment from Amazon, will use it to buy Amazon chips

model-releasesars-technica

Amazon announced a 5 billion investment in Anthropic, with up to 20 billion more tied to commercial milestones. Anthropic committed to spending over $100 billion on AWS technologies over the next deca

Automatic Dataset Construction (ADC): Sample Collection, Data Curation, and Beyond

model-releasesarxiv-cs-lg

arXiv:2408.11338v2 Announce Type: replace-cross Abstract: Large-scale data collection is essential for developing personalized training data, mitigating the shortage of training data, and fine-tuning

Automatic Slide Updating with User-Defined Dynamic Templates and Natural Language Instructions

arXiv:2604.17894v1 Announce Type: new Abstract: Presentation slides are a primary medium for data-driven reporting, yet keeping complex, analytics-style decks up to date remains labor-intensive. Exist

BenchMarker: An Education-Inspired Toolkit for Highlighting Flaws in Multiple-Choice Benchmarks

arXiv:2602.06221v2 Announce Type: replace Abstract: Multiple-choice question answering (MCQA) is standard in NLP, but benchmarks lack rigorous quality control. We present BenchMarker, an education-ins

BIASEDTALES-ML: A Multilingual Dataset for Analyzing Narrative Attribute Distributions in LLM-Generated Stories

arXiv:2604.17008v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly used to generate narrative content, including children's stories, which play an important role in social a

CanonSLR: Canonical-View Guided Multi-View Continuous Sign Language Recognition

arXiv:2604.18184v1 Announce Type: new Abstract: Continuous Sign Language Recognition (CSLR) has achieved remarkable progress in recent years; however, most existing methods are developed under single-

applicationsarxiv-cs-cv

CAPC-CG: A Large-Scale, Expert-Directed LLM-Annotated Corpus of Adaptive Policy Communication in China

arXiv:2510.08986v2 Announce Type: replace Abstract: We introduce CAPC-CG, the Chinese Adaptive Policy Communication (Central Government) Corpus, the first open dataset of Chinese policy directives ann

Capture Timing-Attention of Events in Clinical Time Series

model-releasesarxiv-cs-lg

arXiv:2602.10385v2 Announce Type: replace Abstract: Automatically discovering personalized sequential events from large-scale time-series data is crucial for enabling precision medicine in clinical re

CaseFacts: A Benchmark for Legal Fact-Checking and Precedent Retrieval

arXiv:2601.17230v2 Announce Type: replace Abstract: Automated Fact-Checking has largely focused on verifying general knowledge against static corpora, overlooking high-stakes domains like law where tr

CATP: Confidence-Aware Token Pruning for Camouflaged Object Detection

arXiv:2604.16854v1 Announce Type: new Abstract: Camouflaged Object Detection (COD) aims to segment targets that share extreme textural and structural similarities with their complex environments. Leve

CBR-to-SQL: Rethinking Retrieval-based Text-to-SQL using Case-based Reasoning in the Healthcare Domain

arXiv:2603.05569v2 Announce Type: replace-cross Abstract: Extracting insights from Electronic Health Record (EHR) databases often requires SQL expertise, creating a barrier for clinical decision-makin

applicationsarxiv-cs-cl

CFMS: Towards Explainable and Fine-Grained Chinese Multimodal Sarcasm Detection Benchmark

arXiv:2604.16372v1 Announce Type: new Abstract: Multimodal sarcasm detection has recently garnered significant attention. However, existing benchmarks suffer from coarse-grained annotations and limite

CORP: A Multi-Modal Dataset for Campus-Oriented Roadside Perception Tasks

arXiv:2404.03191v3 Announce Type: replace Abstract: Numerous roadside perception datasets have been introduced to propel advancements in autonomous driving and intelligent transportation systems resea

CRISP: Compressing Redundancy in Chain-of-Thought via Intrinsic Saliency Pruning

arXiv:2604.17297v1 Announce Type: new Abstract: Long Chain-of-Thought (CoT) reasoning is pivotal for the success of recent reasoning models but suffers from high computational overhead and latency. Wh

Decoding AI Tutor Effects for Educational Measurement: Temporal, Multi-Outcome, and Behavior-Cognitive Analysis

arXiv:2604.16366v1 Announce Type: cross Abstract: Artificial intelligence (AI) tutors have become increasingly popular in learning environments. In this study, we propose an AI agent prototype framewo

Differential Privacy in Two-Layer Networks: How DP-SGD Harms Fairness and Robustness

arXiv:2603.04881v2 Announce Type: replace Abstract: Differentially private learning is essential for training models on sensitive data, but empirical studies consistently show that it can degrade perf

DSH-Bench: A Difficulty- and Scenario-Aware Benchmark with Hierarchical Subject Taxonomy for Subject-Driven Text-to-Image Generation

arXiv:2603.08090v2 Announce Type: replace Abstract: Significant progress has been achieved in subject-driven text-to-image (T2I) generation, which aims to synthesize new images depicting target subjec

Dual-Anchoring: Addressing State Drift in Vision-Language Navigation

arXiv:2604.17473v1 Announce Type: new Abstract: Vision-Language Navigation(VLN) requires an agent to navigate through 3D environments by following natural language instructions. While recent Video Lar

agentsarxiv-cs-cv

EgoWalk: A Multimodal Dataset for Robot Navigation in the Wild

arXiv:2505.21282v2 Announce Type: replace Abstract: Data-driven navigation algorithms are critically dependent on large-scale, high-quality real-world data collection for successful training and robus

applicationsarxiv-cs-ro

EvoCoT: Overcoming the Exploration Bottleneck in Reinforcement Learning

model-releasesarxiv-cs-lg

arXiv:2508.07809v5 Announce Type: replace Abstract: Reinforcement learning with verifiable reward (RLVR) has become a promising paradigm for post-training large language models (LLMs) to improve their

Tutorials

Expert-Annotated Embryo Image Dataset with Natural Language Descriptions for Evidence-Based Patient Communication in IVF

arXiv:2604.16528v1 Announce Type: new Abstract: Embryo selection is one of multiple crucial steps in in-vitro fertilization, commonly based on morphological assessment by clinical embryologists. Altho

tutorialsarxiv-cs-cv

Fairness Constraints in High-Dimensional Generalized Linear Models

arXiv:2604.16610v1 Announce Type: cross Abstract: Machine learning models often inherit biases from historical data, raising critical concerns about fairness and accountability. Conventional fairness

Flexible Aspect Ratios ChatGPT Images 2.0 supports aspect ratios as wide as 3:1 and as tall as 1:3. It can generate outputs that are ready t…

Flexible Aspect Ratios ChatGPT Images 2.0 supports aspect ratios as wide as 3:1 and as tall as 1:3. It can generate outputs that are ready to fit the formats you need, from wide banners and presentati

model-releasesopenai--x

From Clinical Intent to Clinical Model: An Autonomous Coding-Agent Framework for Clinician-driven AI Development

arXiv:2604.17110v1 Announce Type: new Abstract: Clinical AI development has traditionally followed a collaborative paradigm that depends on close interaction between clinicians and specialized AI team

agentsarxiv-cs-cv

From Static Inference to Dynamic Interaction: A Survey of Streaming Large Language Models

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

applicationsarxiv-cs-cl

HeLa-Mem: Hebbian Learning and Associative Memory for LLM Agents

arXiv:2604.16839v1 Announce Type: new Abstract: Long-term memory is a critical challenge for Large Language Model agents, as fixed context windows cannot preserve coherence across extended interaction

agentsarxiv-cs-cl

HORIZON: A Benchmark for In-the-wild User Behaviour Modeling

arXiv:2604.17259v1 Announce Type: cross Abstract: User behavior in the real world is diverse, cross-domain, and spans long time horizons. Existing user modeling benchmarks however remain narrow, focus

How Should We Enhance the Safety of Large Reasoning Models: An Empirical Study

arXiv:2505.15404v2 Announce Type: replace Abstract: Large Reasoning Models (LRMs) have achieved remarkable success on reasoning-intensive tasks such as mathematics and programming. However, their enha

HQA-VLAttack: Towards High Quality Adversarial Attack on Vision-Language Pre-Trained Models

arXiv:2604.16499v1 Announce Type: new Abstract: Black-box adversarial attack on vision-language pre-trained models is a practical and challenging task, as text and image perturbations need to be consi