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All news · Today4 items

All AI news

All collected and published items, ordered by time. Picks are a selected subset.
Research

Research papers, technical reports, benchmarks and datasets.

10/11Sun
  1. 量子位71

    He Kaiming team releases VISTA visual harness for multimodal reasoning

    He Kaiming's team published VISTA, a visual-native harness that lets existing multimodal models observe environments, store raw frames outside context, and recall, zoom or inspect them during reasoning without retraining. Paired with VISTA, Claude Opus 5.0 completed all 25 public ARC-AGI-3 games with a perfect 100 action-efficiency score, using 57.4% fewer actions than the human first-play baseline, while GPT-5.6 Sol scored 99. The team also tested browser games, mazes and connect-the-dots tasks, and lists embodied tasks as future work.

  2. 量子位88

    OpenAI Posts Two Kakeya Conjecture Manuscripts, Extending Work to Four Dimensions

    On October 7, OpenAI released 722 mathematics manuscripts, including two on the Kakeya conjecture: a 97-page paper claiming a three-dimensional maximal-function result stronger than Wang and Zahl's, and a 175-page paper claiming the four-dimensional Hausdorff dimension case. Both are attributed to OpenAI, are not Lean-formalized or peer-reviewed, and OpenAI's README says some unformalized results may be flawed.

    Why it matters: The piece traces how two OpenAI manuscripts extend Wang and Zahl's three-dimensional Kakeya work to a stronger maximal-function version and to four dimensions, while noting the proofs lack peer review.

10/10Sat
  1. 雷锋网58

    WorldArena 2.0 Challenge at IROS 2026 Adds Real-Robot and Online RL Tracks

    WorldArena 2.0 Challenge, run by a Tsinghua-led team, released its final leaderboard on September 16 with three tracks covering video quality, world models as reinforcement learning environments, and real-robot manipulation. Visincept's WorldIncept won Track 1, Zhongguancun Academy's MW2 won Track 2, and Xiaomi Robotics' ViTacX topped Track 3, with total prize money of 7,000 USD. Organizers said contact-rich real-robot operation remains a bottleneck.

  2. 雷锋网42

    Columbia's FlexiTac Open-Source Tactile Sensor Platform Hits 1.5 Years

    Columbia University's Li Yunzhu team presented progress on FlexiTac, an open-source flexible piezoresistive tactile sensor platform, at an IROS 2026 workshop. The sensor assembles in 3 minutes, ships with a full BOM and readout software, and integrates with the LeRobot robot-learning framework. Analog Devices is developing a commercial version with tactile resolution five times that of a human finger, produced via semiconductor manufacturing.

  3. Epoch AI · X62

    Epoch AI tracks AI use in arXiv math papers

    Epoch AI reports that in 3 of the 18 math subfields it tracks, more than half of arXiv papers by established authors now acknowledge using AI. It says rates rose rapidly, with differential geometry climbing from about 8% of papers in July to about 57% in September.

  6. Artificial Analysis · X62

    Artificial Analysis tests four image editing models across 30 consecutive edits

    Artificial Analysis tested GPT Image 2.5 Sunburst, Ideogram 4.5, FLUX 3 and Nano Banana 2.1 through 30 consecutive real estate staging edits, finding that Ideogram 4.5 preserved most of the room while the others drifted. Its leaderboard measures single edits, whereas this test fed each model its own previous output. On small edits, Ideogram 4.5 and FLUX 3 left 95% or more essentially untouched; GPT Image 2.5 Sunburst left about a fifth unchanged and drifted most visibly, while Nano Banana 2.1 edited locally but gradually darkened the image.

10/9Fri
  1. 量子位62

    Google and BIDMC study appears in The Lancet: AI chatbot AMIE used for pre-visit assessment

    A study led by researchers from Google and Beth Israel Deaconess Medical Center (BIDMC) appeared in The Lancet’s flagship journal, marking the first time Google research has been published there. In a real-world clinical study at BIDMC’s outpatient primary-care clinic, 98 patients used Google’s research diagnostic AI chatbot AMIE for pre-visit assessment before their emergency visits. Doctors monitored every interaction in real time, and none had to be interrupted under the predefined safety criteria.

  2. 量子位62

    ByteDance Seed finds why DeepSeek-V4 can be inconsistent: chunked KV-cache compression creates position sensitivity

    The ByteDance Seed team found that the DeepSeek-V4 series shows periodic fluctuations in long-context retrieval depending on where information appears, with a cycle of every 4 tokens. In the 128K needle-in-a-haystack test, moving the same information to a different position changed accuracy by as much as 40.2 percentage points.

  4. 量子位62

    MirroS launches AgentGarten: code environments and real-time neural rendering let agents learn by playing

    The MirroS team launched AgentGarten, connecting an executable code environment to a real-time neural renderer: code defines the physics, while the model generates visual feedback, enabling continuous agent interaction at more than 30 fps. In a recreated hide-and-seek experiment, hiders learned to move barriers into cover by round 4, while seekers learned to use a ramp to climb over a wall by round 10; comparable OpenAI experiments in 2019 took about 25 million and 100 million rounds, respectively. The team also published a blog, technical report, code repository, and project site.

  5. 腾讯混元 · X58

    Tencent Hy and universities release ExplorationBench for AI exploration

    Researchers from Tencent Hy, Fudan University, and Tsinghua University released ExplorationBench, a benchmark for measuring how AI systems explore. It uses two verifiable sandboxes, AlienCode with 31 hidden rule changes and 70 tasks, and AlienLogic with 24 patched inference rules and 70 theorems, graded by an interpreter or proof checker rather than an LLM judge. Across 10 frontier systems, feedback beat thinking alone, with the best AlienCode run reaching 89.0% after four rounds.

  6. Sundar Pichai · X66

    Google and BIDMC publish AMIE conversational diagnostics study in The Lancet

    Google and Beth Israel Deaconess Medical Center published an AMIE study in The Lancet, described by Sundar Pichai as the first prospective study of patient-facing conversational diagnostics in a real clinic. In urgent care testing, clinicians said AMIE's summaries helped them prepare for visits in 75% of cases and influenced their approach to care in more than half; its differential diagnoses matched doctors' final diagnoses 90% of the time.

    Why it matters: A prospective clinic study of a patient-facing conversational diagnostic system, with clinician-reported preparation and diagnosis-agreement figures from real urgent care visits.

  7. Epoch AI · X42

    Can AI automate Epoch? We're introducing Epoch Automation Reports to evaluate frontier models on realistic, open-ended tasks drawn from our own work. Claude Fable 5.1 and GPT-6 Astra lead, yet they are far from fully automating Epoch’s work.

    Can AI automate Epoch? We're introducing Epoch Automation Reports to evaluate frontier models on realistic, open-ended tasks drawn from our own work. Claude Fable 5.1 and GPT-6 Astra lead, yet they are far from fully automating Epoch’s work.

10/8Thu
  1. 量子位62

    UniPat AI releases PaperBenchX: GPT-6 Astra fully reproduces only 13.98% of papers

    UniPat AI released PaperBenchX, described as the first end-to-end, multidisciplinary benchmark for reproducing paper results. It builds 93 reproduction tasks from 93 papers, spanning 12 research areas including electromagnetics, photonics, chemistry, materials, biology, and robotics, across 10 field-native scientific environments, with 3,168 expert-verified scoring criteria.

  2. 雷锋网44

    Galaxy General, Tsinghua, and collaborators propose LATENT, teaching humanoids tennis from imperfect human data

    The GaLbot team at Galaxy General, together with Tsinghua, Peking University, and others, proposed LATENT, which trains humanoid robots to play tennis using about five hours of imperfect motion data from five amateur players. The method first trains a motion tracker and compresses it into a latent action space with a Latent Action Barrier constraint. On a Unitree G1, it achieved a 90.90% success rate on real forehands and 77.78% on backhands.

  5. vLLM · X62

    vLLM-Omni technical report proposes a unified serving runtime for omni-modality generation

    The vLLM project shared the vLLM-Omni technical report, describing a unified serving runtime for omni-modality generation. It argues that speech assistants, visual generation, world models and robot loops diverge from a single text decode loop into multi-stage autoregressive pipelines, iterative diffusion and stateful sessions, which LLM servers and diffusion stacks each cover only partially. vLLM-Omni acts as a shared control plane with an orchestrator, specialized engines, a connector and one session path. Paper and repo links are included.

  7. Google Research62

    Google Research's three-month patent-writing experiment found AI boosted output but did not accelerate junior lawyers' independent judgment

    Google Research published a three-month field experiment on patent drafting through NBER. It randomly gave 133 lawyers at 11 intellectual-property law firms access to an unpublished Google Labs AI patent-writing assistant, now part of Gemini Notebook; two-thirds received early access.

    Why it matters: The three-month patent-writing experiment separates AI's immediate productivity gains from changes in unaided judgment, providing comparative evidence on AI's effect on professional skills.

  8. NVIDIA AI · X38

    An AI agent makes a mistake early in a task, then keeps going in the wrong direction. Our researchers built PivotOPD to teach agents how to avoid those mistakes and recover when they happen. During training, a teacher model shows the agent a better action and how to get back on https://t.co/7hMLMdExEH

    An AI agent makes a mistake early in a task, then keeps going in the wrong direction. Our researchers built PivotOPD to teach agents how to avoid those mistakes and recover when they happen. During training, a teacher model shows the agent a better action and how to get back on https://t.co/7hMLMdExEH

  9. Epoch AI · X35

    AI developers aim to create an automated AI researcher. How close are they? To find out, we built InnovationEval, which tests whether AI can produce post-training innovations comparable in magnitude to a recently published advance. So far, agents’ results are underwhelming.

    AI developers aim to create an automated AI researcher. How close are they? To find out, we built InnovationEval, which tests whether AI can produce post-training innovations comparable in magnitude to a recently published advance. So far, agents’ results are underwhelming.

  10. Epoch AI · X20

    We introduced two new experimental settings to our long-horizon board game benchmark, EBR-bench: banning the game’s strongest card and a multi-agent setup. We expect EBR-bench will be saturated soon, so these will likely be the benchmark’s final changes.

    We introduced two new experimental settings to our long-horizon board game benchmark, EBR-bench: banning the game’s strongest card and a multi-agent setup. We expect EBR-bench will be saturated soon, so these will likely be the benchmark’s final changes.

10/7Wed
  1. Hugging Face Blog62

    Nemotron fine-tuning reaches gold-medal level at both IOI 2026 and IMO 2026

    The NVIDIA team started with Nemotron 3 and used supervised fine-tuning, reinforcement learning, and a generate-verify-improve reasoning process to build specialized models that reached gold-medal thresholds at both IOI 2026 and IMO 2026.

    Why it matters: The source gives a complete recipe for fine-tuning Nemotron 3 to gold-medal-level results at IOI and IMO, which readers can use to reproduce its data and reasoning workflow.

  2. Latent Space88

    OpenAI's internal model releases 722 math papers, claiming to solve 90 of 500 open problems

    OpenAI published mathematical results from an unreleased internal frontier model through a blog, GitHub repository, and posts. The release includes 722 manuscripts grouped into 372 related result families, drawn from an evaluation of about 4,000 research questions. Each result used an average of about three hours of ChatGPT Pro reasoning compute.

    Why it matters: OpenAI is producing mathematical results in bulk with an internal model, giving readers a view of the scale, compute cost, and outside criticism surrounding the work.

  3. 量子位85

    OpenAI releases 722 math manuscripts covering the Riemann, Hodge, and BSD conjectures

    OpenAI released 722 mathematical manuscripts grouped into 372 result clusters. They all came from an unreleased internal model, and the papers, source code, and some Lean proofs have been uploaded to GitHub. Topics include the quasi-Riemann hypothesis, Hodge conjecture, BSD conjecture, and the irrationality measure of π, spanning 17 areas. OpenAI says the model attempted about 4,000 research questions, with compute for each result averaging about three hours of ChatGPT Pro reasoning.

    Why it matters: OpenAI released 722 mathematical manuscripts at once across several areas related to Millennium Prize problems, while surfacing concerns in the mathematics community about verification and reading burden.

  4. Greg Brockman · X70

    OpenAI releases a batch of mathematical results from an internal frontier model

    OpenAI released new mathematical results produced by an internal frontier model, with related code and results at github.com/openai/math. OpenAI said it consulted an independent advisory group on mathematics and AI at the Institute for Advanced Study in Princeton about how to publish the work and considered its recommendations. Greg Brockman reposted the announcement, saying it points toward accelerating scientific discovery and improving quality of life for everyone.

    Why it matters: OpenAI made a batch of mathematical results from an internal frontier model public and said it followed advice from an external advisory group on the release.

  5. The Verge · AI78

    OpenAI publishes 722 math manuscripts, saying they solve hundreds of open problems

    OpenAI published 722 manuscripts across 372 result families. According to the newly formed independent advisory group AGMAI, the collection includes answers to hundreds of open problems, produced by an unreleased frontier model.

    Why it matters: OpenAI released 722 mathematical manuscripts at once, giving readers a view of the work's scale, publication method, and debate over research ethics.

  7. OpenAI · X62

    OpenAI releases mathematical results from an internal frontier model

    OpenAI released a batch of mathematical results produced by an internal frontier model, with related code and materials hosted at github.com/openai/math. OpenAI said it consulted an independent advisory group on mathematics and AI at the Institute for Advanced Study in Princeton and considered its recommendations and public guidance when deciding how to publish the work.

10/6Tue
  2. The Decoder62

    Researchers extend LeCun's JEPA into JEPA-Anything, a world model spanning physical and biological domains

    Researchers at PhAI Labs, Stanford, Oxford, and Princeton proposed JEPA-Anything. It splits JEPA's predicted state into four orthogonal factors, assigns a prediction module to each, and recombines them. It outperformed standard JEPA with the same architecture and data on ten test tasks in physics, robotics, weather, and other areas.

  3. Google Research31

    Google publishes workshop report on open questions in agent privacy and security

    Google published the workshop report Open and Emerging Issues in Agentic Privacy and Security: A Contextual Perspective, compiled by more than 50 academics and industry participants at a Google CAPS workshop in New York in late 2025. Based on Contextual Integrity (CI) theory, the report proposes a context-policy engine as an oversight layer to assess whether information flows are appropriate before data leaves a user's workspace. It addresses prompt injection, probabilistic control flow, and autonomous delegation at three levels: system-level sandboxing, model-level reasoning, and user control.

  4. Simon Willison22

    Benchmark tests whether Qwen3.8 27B can add using English number words

    A benchmark tested the local Qwen3.8-27B-Q4_K_M.gguf on 5,070 cases without reasoning, asking it to add positive integers using only English words and return exact results. It achieved 23.57% numerical accuracy and 96.17% format compliance. Accuracy fell as the numbers grew, from 97.04% on one- to three-digit numbers to 6.44% on ten- to thirteen-digit numbers. In 169 paired cases with medium reasoning enabled, the model answered 167 correctly.

  5. Google AI · X62

    Gemma 4 and BOTANIC-1 rank plant mutations in minutes

    Google AI highlights work by AI research lab Living Models, which paired Gemma 4 with BOTANIC-1, a model trained on plant DNA from 320 species, to identify mutations that alter crop traits. In a melon yield gene test, the pair ranked the target mutation first out of 2,494 possibilities in under four minutes, versus years of physical breeding trials. A demo and paper are linked.

10/5Mon
10/4Sun