AI helps design new materials that work in the real world
MIT researchers added a new component to AI models that design new materials, helping ensure the material will be stable and practical for real-world use. The “CrysVCD” approach c…
Generating scenarios for extreme events, without extreme data
MIT engineers developed a tool that predicts plausible extreme events and worst-case scenarios, such as an extreme storm’s likely duration, intensity, and area of impact. Importan…
Paving the way for greener ammonia production
Ammonia is essential for fertilizer, but its production generates about 1.5 percent of global greenhouse gas emissions. MIT’s Bilge Yildiz and colleagues have developed a computat…
When AI art has no author: Study finds generated images often can’t be traced to training data
Images generated by AI models trained on massive datasets often can’t be traced to specific training images, MIT CSAIL researchers found. Removing individual images from the datas…
The benefits of medical AI assistance vary based on user expertise
New research found non-experts deferred to AI-based assistance in diagnosing skin cancer, even when it was wrong, while clinicians were more likely to catch AI errors.
Alexander Rakhlin named director of the MIT Statistics and Data Science Center
Alexander ‘Sasha’ Rakhlin, the Distinguished Professor in Data, Systems, and Society, IDSS and Brain and Cognitive Sciences at MIT, has been named the next director of the MIT Sta…
AI research papers and lab updates — page 2
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How researchers adapted Dolma for better Thai language models
Thai researchers adapted Ai2’s open Dolma toolkit to build Mangosteen, a 47-billion-token Thai corpus that filters low-quality web data while maintaining or improving model perfor…
How a Georgia Tech team used the open Olmo stack to trace social reasoning
A Georgia Tech team used Ai2’s fully open Olmo stack to trace social reasoning back to the training data that shaped it, finding that dialogue-rich, interpersonal writing had an o…
When a model reads a drug's class from its name—not its knowledge
Researchers used Olmo 3 and its open training data to show that models can infer a drug’s class from its name instead of knowing the specific medication, and traced that shortcut…
TutorMoments: Do AI tutors know when to help and when to hold back?
TutorMoments is an open, replay-based evaluation framework that tests whether AI tutors can recognize when to support a student and when to hold back and encourage deeper reasonin…
Ai2 expands collaboration with Hugging Face to accelerate open science
Ai2 is expanding its partnership with Hugging Face to give its growing portfolio of fully open models, datasets, benchmarks, and applications the storage, bandwidth, and integrati…
Tracing distinctive language in AI-written text
Stony Brook researchers used our infini-gram engine to trace distinctive phrases in AI-generated writing back to existing sources, finding that top-selling self-published books on…
IDEA Prune: An Integrated Enlarge-and-Prune Pipeline in Generative Language Model Pretraining
Recent advancements in large language models have intensified the need for efficient and deployable models within limited inference budgets…
PROOF-Gen: From Optimized Data to Better Distillation
Supervised fine-tuning on teacher-generated trajectories is the standard first stage for distilling tool-calling capabilities into…
Luce: Relightable Gaussians for 3D Asset Generation
High-fidelity image-to-3D generation requires a 3D representation that captures both geometry and appearance. To support relighting and…
STARFlow2: Bridging Language Models and Normalizing Flows for Unified Multimodal Generation
Unified multimodal models that understand, reason over, and generate interleaved text–image sequences remain structurally fragmented:…
Beyond Visual CoT: Internalized Visual Thinking for Proactive Video Reasoning
Multimodal large language models increasingly use visual chain-of-thought (Visual CoT) to reason about spatial, temporal, and embodied…
Multilingual Knowledge Transfer under Data Constraints via Lexical Interventions
Cross-lingual knowledge transfer is critical for building high-performing multilingual language models for languages with insufficient…
AgentHands: Generating interactive hand gestures for spatially grounded agent conversations in XR
An AI tool for prioritizing candidate biomarkers from wearable sensor data
How mobility gives language models a deeper understanding of place
Seeing beyond BMI: Estimating cardiometabolic risk with smartphone imagery
Generating scenarios for extreme events, without extreme data
MIT engineers developed a tool that predicts plausible extreme events and worst-case scenarios, such as an extreme storm’s likely duration, intensity, and area of impact. Importan…
Paving the way for greener ammonia production
Ammonia is essential for fertilizer, but its production generates about 1.5 percent of global greenhouse gas emissions. MIT’s Bilge Yildiz and colleagues have developed a computat…
SOP-Bench: A new benchmark for evaluating AI agents on real business procedures
Extendable framework enables testing agents on the full set of capabilities required to successfully complete a procedure, not isolated proxy tasks.
A decade of mathematical certainty: Reflections on the Automated Reasoning Group
Byron Cook reflects on 10 years of using mathematical proof to verify AWS infrastructure, from IAM Access Analyzer to AI guardrails.
AWS Trainium Frontier competition: Co-design models and kernels on purpose-built AI chips
A competition with a finalist ceremony during NeurIPS 2026, challenging researchers to train language models from scratch on Trainium, exploring what optimal architectures look li…
34 Amazon Research Awards Build on Trainium recipients announced
Amazon announces 34 recipients of the Build on Trainium program, a $110 million credit initiative supporting AI research at 30 universities including Stanford, UC Berkeley, UIUC,…
From Atari to EVE Online: Building on 15 Years of AI Research in Games
Google DeepMind partners with game developers to build generalist agents like SIMA 2 and unlock breakthrough gameplay experiences across persistent worlds.
Introducing Gemini 3.7 Flash
Gemini 3.7 Flash is our most intelligent workhorse model yet for coding and agents.
Putting sign language AI into users’ hands
Discover our new sign-language-to-text (SL2T) translation model, bringing ASL dictation to Gboard and Live Transcribe on Pixel 11.
Broadening access to Skala creates a faster path to predictive DFT
Skala 1.1, the updated deep-learning exchange-correlation functional from Microsoft Research, provides greater accuracy, expanded accessibility across the computational chemistry…
MindTopo reveals VLMs’ spatial reasoning abilities
A path, a fence, a knot. MindTopo sets a new benchmark for testing how AI understands topological relationships and highlights new opportunities to strengthen spatial reasoning an…
Introducing CARE-X: Towards Clinically Useful Radiology VLMs with Auxiliary Supervision, Reward-Aligned Learning, and Tool-Augmented Measurement
Radiology AI is evolving beyond report generation. CARE-X explores a unified approach that combines flexible reasoning, calibrated predictions, and measurement-based tools for che…
Orchard: An open framework for scalable agentic AI
Orchard is an open-source framework for the research community to train and evaluate AI agents across task types. It reduces complexity while supporting strong performance from sm…
Neutrinos From Deep Inside Earth Provide a New Picture of the Mantle
A global constellation of neutrino detectors is creating a never-before-seen view of the radioactive elements that power Earth’s tectonic heat engine.
How Does Touch Lead To Pain Or Pleasure?
Neuroscientist Ishmail Abdus-Saboor discusses efforts to understand how skin contact can be painful or pleasurable, and what touch-obsessed naked mole rats might teach us about hu…
Corals Spin Tiny Vortices to Get Oxygen, but Not if It’s Too Hot
New research is helping biologists understand how an overlooked aspect of coral physiology may affect their fate under climate change.
Why the Legendary Erdős Problems Are Falling to AI
AI’s greatest mathematical successes have come from answers to problems posed by a mid-20th century iconoclast. By examining what makes the Erdős problems unique, mathematicians a…
Is AI Reasoning Right for the Wrong Reasons?
The idea that artificial intelligence can “reason” is more intuitive than ever. But intuitions can be wrong, and the science is far from settled.
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