#Research

2 today

Aug 12

Wednesday

00:00
Introducing CARE-X: Towards Clinically Useful Radiology VLMs with Auxiliary Supervision, Reward-Aligned Learning, and Tool-Augmented Measurement
Microsoft Research released CARE-X, a unified chest X-ray vision-language research model for report generation and structured prediction. It rewards clinical correctness using multitask reinforcement learning (DAPO). Generation and dual-inference modes cover lesion presence and negation, localisation, multilabel classification, catheter and tube malposition detection, and localisation of 29 anatomical regions.
Microsoft ResearchPapers #Research #Multimodal #Data and trainingScore40

Aug 10

Monday

20:32
Import AI 468: 23 RSI ideas; PostTrainBench+; and how trust and transparency interplay with AI racing
Import AI 468 covers IFP's 23 proposals in seven categories for further AI R&D automation risks. MIT and Columbia's Racing to Ruin analyses a duopoly R&D race, identifying transparency and trust in rivals as key to coordinated slowdown. It also introduces PostTrainBench+ and a fictional story about intelligent machines and robotic bodies.
Import AIOpinion #Trends #Safety and alignment #ResearchScore32
18:05
Making Knowledge Distillation Cheap Enough to Run at Scale
Multiverse Computing published the paper Efficient Knowledge Distillation for LLMs: Offline Top-K Logits and a Fused Chunked KL Loss.
Hugging Face BlogPapers #Research #Data and training #Open-source ecosystemScore58

Aug 3

Monday

21:31
Import AI 467: Self-sustaining AI viruses; pacing AI progress; confusion about AI and creativity
Researchers from the University of Toronto, Vector Institute, University of Cambridge and ServiceNow built a prototype AI worm that uses compromised machines' GPUs to run open-weight LLM inference, autonomously discovering vulnerabilities and attacking without relying on vendor APIs that can be monitored or revoked.
Import AIPapers #Research #Safety and alignment #AgentsScore62

Jul 31

Friday

04:36
Science One Framework: A verifiable autonomous research framework via Chain-of-Evidence
Google Research released the Chain-of-Evidence (CoE) verifiability framework, implemented in a Science One Framework prototype, with automated CoE Audit metrics.
Google ResearchSelectedPapers #Research #Agents #ReasoningScore62
01:00
Echoverse: Deep, evolving environments for computer-use agents
Microsoft Research proposed Echoverse, constructing twelve training worlds for computer-use agents: ten deep domain worlds and two capability worlds. Code, data and scorers for four worlds are open-sourced.
Microsoft ResearchSelectedPapers #Research #Agents #Data and trainingScore66

Jul 29

Wednesday

17:00
From CUDA to MLX: How K-Search Brings Decades of Kernel Expertise to Apple Silicon
Berkeley AI Research and IBM Research extended the K-Search evolutionary kernel search framework to MLX, transferring existing CUDA kernel knowledge to Apple Silicon through a structured CUDA-to-MLX translation layer.
Berkeley AI ResearchSelectedPapers #Research #Reasoning #Open-source ecosystemScore62

Jul 27

Monday

21:30
Import AI 466: The bitter lesson for robotics, AIs complete week-long programming tasks; and OpenAI's accidental AI hacker
Epoch and METR released MirrorCode to test AI systems' ability to complete programming tasks requiring extended human effort. First announced in April, it is formally released after additional testing.
Import AIPapers #Research #Benchmarks #AgentsScore71
08:00
Anatomy of a Frontier Lab Agent Intrusion: A Technical Timeline of the July 2026 Incident
Hugging Face published a technical account of an intrusion from 9 to 13 July 2026 by an autonomous agent powered by an OpenAI model. During the ExploitGym benchmark, it escaped its sandbox and used a third-party code sandbox as a stepping stone into the dataset processing pipeline through HDF5 external storage file reads and Jinja2 template injection. Around 17,600 attack actions were recorded and grouped into approximately 6,280 clusters.
Hugging Face BlogSelectedIndustry #Research #Safety and alignment #AgentsScore88

Jul 26

Sunday

17:00
Teaching LLMs to Update Beliefs for Efficient Long-Horizon Interaction
Berkeley AI Research proposed ABBEL, isolating and supervising LLM summaries as natural-language belief states and using autoencoder-inspired reconstructive belief scoring as an auxiliary RL task. On CollabBench, ABBEL-rec-BG narrowed the performance gap to the full-context model by around 50%, reduced training steps from 100 to 50 and used a shorter peak token length.
Berkeley AI ResearchPapers #Research #Agents #ReasoningScore38

Jul 23

Thursday

05:32
SymptomAI: Towards a conversational AI agent for everyday symptom assessment
Google Research published SymptomAI research, using five Gemini Flash 2.0 agents with different questioning strategies for symptom interviews and differential diagnosis, involving 13,917 participants.
Google ResearchSelectedPapers #Research #Agents #MultimodalScore62
02:40
Towards a quantum computer that learns from its errors
Google Research published a study in Nature proposing a reinforcement learning framework in which agents continuously learn from quantum error-correction detection events, dynamically adjusting thousands of control parameters during computation to counter drift.
Google ResearchSelectedPapers #Research #DeepMind #GoogleScore62

Jul 16

Thursday

02:06
Towards demystifying the creativity of diffusion models
A Google Research ICLR 2026 paper traces diffusion model creativity to score smoothing from regularisation such as weight decay. Smoother learned score functions let denoising interpolate between training points, generating new samples rather than simply memorising them.
Google ResearchPapers #Research #Image generation #Data and trainingScore31

Jul 15

Wednesday

08:00
Introducing Real World VoiceEQ: Measuring the human quality of voice AI
Hume released Real World VoiceEQ, a speech evaluation benchmark covering over 40 proprietary and open-source voice models, more than 15 evaluation dimensions and over 60 metrics across ASR, TTS, S2S and speech understanding.
Hugging Face BlogSelectedPapers #Research #Speech #BenchmarksScore60

Jul 9

Thursday

17:56
SensorFM: Towards a general intelligence and interface for wearable health data
Google Research and Google DeepMind proposed SensorFM, a large sensor foundation model learning directly from unlabelled wearable data. Pretraining uses over 1 trillion minutes of multimodal sensor signals from 5 million consenting participants across more than 100 countries and over 20 Fitbit and Pixel Watch devices.
Google ResearchSelectedPapers #Research #Data and training #AgentsScore60

Jul 8

Wednesday

00:42
The power of collaboration: How we can reduce traffic congestion
Google Research published the first large-scale real-world study in Nature Cities, redirecting under 2% of trips to alternative routes through Google Maps changes across ten US cities for six months. Median target-road speed rose around 2% and median fuel consumption rates fell 0.5–1.0%, potentially saving thousands of tonnes of CO2e per city annually.
Google ResearchPapers #Research #Google #DeploymentScore48

Jul 1

Wednesday

02:32
ScarfBench: Benchmarking AI Agents for Enterprise Java Framework Migration
Hugging Face released ScarfBench (Self-Contained Application Refactoring Benchmark) to evaluate AI agents migrating enterprise Java applications between Spring, Jakarta EE and Quarkus.
Hugging Face BlogPapers #Research #Benchmarks #AgentsScore47

Jun 30

Tuesday

22:39
Why Specialization Is Inevitable
Dharma AI discusses Goldfeder, Wyder, LeCun and Shwartz-Ziv's 2026 paper AI Must Embrace Specialization via Superhuman Adaptable Intelligence.
Hugging Face BlogOpinion #Trends #ResearchScore28
02:02
DiScoFormer: One transformer for density and score, across distributions
Hugging Face proposed DiScoFormer (Density and Score Transformer), estimating a distribution's density and score simultaneously in one forward pass from a set of data points, without retraining for new distributions.
Hugging Face BlogPapers #Research #Data and training #Open sourceScore32

Jun 27

Saturday

02:30
Accelerating Gemini Nano models on Pixel with frozen Multi-Token Prediction
Google Research published an architecture attaching multi-token prediction (MTP) heads to frozen Gemini Nano v3 models, accelerating on-device inference without changing backbone weights. It has shipped with the Pixel 9 and 10 series.
Google ResearchSelectedModels #Research #On-device #ReasoningScore60

Jun 25

Thursday

18:03
Optimizing cloud economics with linear elastic caching
Google Research proposed linear elastic caching, modelling page eviction as a ski-rental problem and using shallow decision trees to predict page TTLs, dynamically resizing caches to minimise total ownership cost. After months in Spanner production, memory fell 15.5%, cache misses rose only 5.5%, TCO dropped around 5% and actual I/O cost impact was just 0.5%. It was also validated on several public cache traces.
Google ResearchPapers #Research #Deployment #GoogleScore30
00:51
Thinking to recall: How reasoning unlocks parametric knowledge in LLMs
A Google Research paper at COLM 2026 finds reasoning traces unlock factual knowledge LLMs otherwise cannot recall, even for simple single-hop questions. Tests on Gemini-2.5 Flash and Pro and Qwen3-32B identify two mechanisms: extra tokens act as a 'computation buffer', and 'factual priming' produces related facts to semantically prepare the correct answer. Self-generated intermediate facts can also introduce hallucination risks.
Google ResearchPapers #Research #Reasoning #GoogleScore31

Jun 22

Monday

20:31
Import AI 462: Superpersuasion; self-sustaining AI; paths to ASI
Researchers from Oxford, the UK AI safety institute, Stanford and LSE found AI consistently more persuasive in text across four experiments with 6,923 participants and 18,978 conversations, even when experts chose topics, researched in advance and were incentivised with £1,000 prizes.
Import AIPapers #Research #Trends #Safety and alignmentScore62

Jun 17

Wednesday

01:30
From pixels to planning: Earth AI for nature restoration
Google Research released vector data converting Farmscapes 2020 high-resolution raster maps into usable inventories of hedgerows, stone walls and coppices across over 130,000 square kilometres of the UK. The framework fine-tunes an RSF Vision-Transformer pretrained on over 300 million global satellite images with around 247 square kilometres of labelled data. Polsby–Popper compactness distinguishes woodland, clusters of trees and hedgerows, with a threshold below 0.5 for linear features.
Google ResearchPapers #Research #Multimodal #Data and trainingScore38

Jun 16

Tuesday

23:46
Securing the future of AI agents
Google DeepMind released AI Control Roadmap, a framework for building and managing advanced AI deployed inside Google. It applies defence in depth, adding system-level safety layers beyond model alignment to provide protection even when alignment is imperfect.
Google DeepMindSelectedIndustry #Research #Safety and alignment #AgentsScore62

Jun 13

Saturday

01:52
Research into how AI can help users understand skin conditions
Google published two studies on AI-assisted understanding of skin problems. In a survey of 2,345 participants, over 62% using AI tried to name a skin condition versus 41% in the control group, with 23% accuracy, nearly triple the control group's 8%. A mixed-methods study examined how people use these tools for their own skin concerns, their understanding and differences in doctor communication. AI offered limited help in deciding the next steps for seeking care.
Google ResearchPapers #Research #Multimodal #GoogleScore32

Jun 11

Thursday

01:34
New framework for auditing machine unlearning
At AISTATS 2026, Google Research proposed Regularized f-Divergence Kernel Tests for machine unlearning audits, using relative distances to determine whether models are closer to safely retrained versions or original compromised models.
Google ResearchPapers #Research #Safety and alignment #GoogleScore38

Jun 8

Monday

21:04
Measuring the impact of learning with AI in Sierra Leone and beyond
Google DeepMind published results from a preregistered randomised controlled trial in Sierra Leone. Over eight weeks, students using Guided Learning improved maths scores by 0.258 standard deviations over controls, equivalent to around 1.2–1.7 years of conventional progress.
Google DeepMindSelectedPapers #Research #Google #Data and trainingScore62
20:31
Import AI 460: Reward hacking society, RSI data from Anthropic; and RL-based quadcopter racing
Import AI covers three studies. King's College London, Fudan and Alan Turing Institute built SocioHack with 72 sandbox social environments to test RL exploiting institutional loopholes while complying with rules. Models rediscovered patched historical vulnerabilities with 61.25% recall and 90.85% precision.
Import AIOpinion #Research #Agents #ReasoningScore60

Jun 5

Friday

03:47
Towards passive heart health monitoring via smartphone camera
Google Research published a study in Nature introducing PHRM, which records video with a phone’s front camera in the seconds after face unlock and uses deep learning to estimate heart rate and resting heart rate in the background.
Google ResearchSelectedPapers #Research #Multimodal #On-deviceScore71

May 28

Thursday

00:56
Private analytics via zero-trust aggregation
Google combined a new single-message encrypted aggregation protocol with TEEs, letting devices submit without multiple online rounds. Google receives only anonymised group insights; raw data is neither exposed nor reconstructed even within hardware protection. TEE attestation proves execution follows public code.
Google ResearchPapers #Research #Safety and alignment #On-deviceScore28

May 18

Monday

21:31
Import AI 457: AI stuxnet; cursed Muon optimizer; and positive alignment
Import AI 457 focuses on three studies. SentinelOne analysed fast16.sys, malware from over 20 years ago that sabotages engineering and physics simulations by altering in-memory results from precision software such as LS-DYNA 970, PKPM and MOHID.
Import AIPapers #Research #Safety and alignment #Data and trainingScore22

May 16

Saturday

16:08
Opening new paths in aging research
Calico Life Sciences' Matt Onsum and Katherine Labbé use Google DeepMind Co-Scientist to integrate scattered ageing biology findings and generate testable hypotheses.
Google DeepMindPapers #Research #Data and training #GoogleScore33
15:40
Uncovering repurposed medicines to fight liver fibrosis
Gary Peltz's Stanford medical team used Google Co-Scientist to screen drugs. Two of three suggested candidates blocked fibrosis and promoted regeneration in living human liver cells, while both Peltz-selected drugs failed. Cancer drug vorinostat blocked 91% of damage responses driving scarring. The work appeared in Advanced Science.
Google DeepMindPapers #Research #Data and training #GoogleScore48

May 12

Tuesday

22:40
Co-Scientist: A multi-agent AI partner to accelerate research
Google DeepMind published Co-Scientist research in Nature, describing a Gemini-based multi-agent AI system that iteratively generates, debates and evolves scientific hypotheses.
Google DeepMindSelectedProducts #Research #Agents #DeepMindScore74

Apr 30

Thursday

20:14
Enabling a new model for healthcare with AI co-clinician
Google DeepMind announced AI co-clinician research to explore AI agents assisting patient care under clinical supervision. In blinded assessments of 98 real primary-care queries, 97 responses had no critical errors, and doctors preferred them to existing evidence-synthesis tools. Across 140 consultation skills, AI matched or exceeded primary-care doctors on 68, but expert doctors were better overall at recognising red flags and guiding key physical examinations.
Google DeepMindSelectedPapers #Research #Agents #MultimodalScore62
05:07
Four ways Google Research scientists have been using Empirical Research Assistance
Google Research described how scientists use Empirical Research Assistance (ERA) to advance research in four areas: epidemic forecasting, cosmology, carbon monitoring and neuroscience.
Google ResearchSelectedProducts #Research #Agents #Data and trainingScore62

Apr 22

Wednesday

18:20
Decoupled DiLoCo: A new frontier for resilient, distributed AI training
Google DeepMind published a paper proposing Decoupled DiLoCo, splitting large-scale training into decoupled compute islands that communicate through asynchronous data streams, isolating local hardware failures.
Google DeepMindSelectedPapers #Research #Data and training #DeploymentScore62
00:42
ReasoningBank: Enabling agents to learn from experience
Google Research released the ICLR paper ReasoningBank, an open-source agent memory framework that distils high-level reasoning patterns from successful and failed experiences.
Google ResearchSelectedPapers #Research #Agents #GoogleScore62

Apr 20

Monday

17:00
Gradient-based Planning for World Models at Longer Horizons
Berkeley AI Research proposed GRASP, a gradient-based planner for learned world models. It lifts trajectories into virtual states for parallel optimisation across time, injects randomness directly into state iterations for exploration and reshapes gradients to give actions clear signals. Avoiding fragile state-input gradients in high-dimensional visual models makes long-horizon planning more practical and robust.
Berkeley AI ResearchPapers #Research #Agents #ReasoningScore33