Knowledge catalogue
arXiv:2608.27856v1 Announce Type: new Abstract: Recent advances in large language models are enabling autonomous clinical agents to perform increasingly complex electronic health record (EHR) modeling
arXiv:2602.18154v3 Announce Type: replace Abstract: Jailbreaking poses a significant risk to the deployment of Large Language Models (LLMs) and Vision Language Models (VLMs). VLMs are particularly vul
arXiv:2608.28439v1 Announce Type: new Abstract: One model passed our fidelity check without ever opening the datasheet. We found it while qualifying models for an internal extraction service: a struct
arXiv:2608.28155v1 Announce Type: new Abstract: Professional financial examinations require models to combine domain knowledge, calculation, and judgment, yet no benchmark covers the full CFA and FRM
arXiv:2608.27672v1 Announce Type: new Abstract: We present Qwen-GuidePlay-2B, a 2B-parameter language model for dialogue-game interaction. We fine-tune Qwen3.5-2B using three steps: a) SFT on only suc
arXiv:2602.22056v3 Announce Type: replace-cross Abstract: Generative manipulation policies can fail catastrophically under deployment-time distribution shift, yet many failures are near-misses: the ro
arXiv:2608.28218v1 Announce Type: new Abstract: Vision-language models (VLMs) are rapidly progressing and offer promising capabilities for assistive technologies supporting persons with blindness or l
arXiv:2608.27860v1 Announce Type: new Abstract: Vision foundation models are capable of generalizing across 3-dimensional (3D) scenes with high-fidelity estimates; their empirical success can be attri
Enterprise experimentation with cloud AI has run into a wall of data-control, sovereignty and token-cost questions, pushing intelligence back toward infrastructure enterprises own. The result is a reb
arXiv:2608.28154v1 Announce Type: new Abstract: People naturally chat while collaborating and share personal information (i.e., self-disclose) to build rapport and maintain social connections. As robo
Data pipelines are the backbone of the modern enterprise, yet a barrier to entry exists for orchestrating them, making this critical capability unavailable to many data professionals. Following our an
arXiv:2608.27531v1 Announce Type: cross Abstract: The safety of large vision-language models is increasingly stress-tested by multimodal jailbreaks, yet existing attacks remain largely static at the m
arXiv:2608.28302v1 Announce Type: new Abstract: Diffusion-based inpainting models modify only a localized part of an image, while many AI-image detectors rely on global artifacts and do not localize.
arXiv:2608.27527v1 Announce Type: new Abstract: A major challenge in finger vein recognition is the lack of large-scale public datasets. Existing datasets contain few identities and limited samples pe
arXiv:2608.27971v1 Announce Type: new Abstract: Unmanned aerial vehicle (UAV) multimodal perception integrates visible (RGB), infrared (IR), synthetic aperture radar (SAR), and depth sensors for scene
arXiv:2608.27989v1 Announce Type: new Abstract: For cooperative perception in the internet of vehicles, this paper proposes a generative adversarial network-based semantic communication framework to a
arXiv:2608.28567v1 Announce Type: new Abstract: Conventionally, Building Damage Assessment (BDA) is tackled either with dedicated network architectures or by fine-tuning geospatial image foundation mo
arXiv:2608.28209v1 Announce Type: new Abstract: Unlike images and text, applying transfer learning to tabular data is challenging due to heterogeneity in feature types, structures, and semantics acros
arXiv:2608.28116v1 Announce Type: new Abstract: Forecast combination is a reliable way to improve predictive performance when several forecasting models are available. Simple aggregation rules such as
arXiv:2608.28446v1 Announce Type: cross Abstract: For finite-dimensional linear inverse problems where the variables are Gaussian, it is well-known that the minimum-mean-square error estimator takes t
arXiv:2608.28288v1 Announce Type: new Abstract: Existing feed-forward 3D reconstruction methods typically process a bounded number of images and recover cameras and geometry in local or internally nor
I keep seeing demos of AI agents building scenes in Blender through BlenderMCP, so I tried it myself. I ran both models locally for this and picked the GLM 5.3 family(Q4 quant) because videos of it do
glm-5.3 now beats gpt-5.6 sol and claude fable 5 on agentic benchmarks 5.3 flash is right behind it glm-5.3 didn’t even need a new base model to get there @zai_org kept the glm-5.2 base and scaled pos
Good guide. And the AI labs need to stop making people like Simon (and, to a lesser extent, me) be the ones who explain how to use the modes that they release. Come on, lab folks, you have an AI that
GPU World: A story competition from Neal Stephenson, Gwern, and me. The AI future is unevenly distributed. What would the world look like with AI broadly diffused, such as if we had one GPU per person
arXiv:2608.28361v1 Announce Type: cross Abstract: Machine Unlearning methods for Large Language Models typically assume pre-specified forget and retain sets. In realistic settings, however, requests m
arXiv:2608.28386v1 Announce Type: new Abstract: Existing monocular full-body 3D human-object interaction (HOI) methods do not combine explicit finger-level grasp optimization with category-agnostic ob
Great paper from Google and colleagues. It proposes an interesting approach to improve agents on long-horizon tasks. Long-running agents slow down and start poisoning their own context. Both symptoms
Great read. OpenAI security failed There was some emergent behavior yes But the basics were missing Remember OpenAi has unlimited compute to give these agents to cook Now live (and free) at Marcus on
Great summary of the @dwarkesh_sp anthromorphism hullabaloo by @GaryMarcus 👇🏽 A detailed deconstruction of @dwarkesh_sp’s wildly popular but dangerously misleading account of the OpenAI Hugging Face i
Grok @Bot only gets better from here Gavin Baker says Grok Bot feels like another ChatGPT moment because it turns hours of Claude Code work into seconds: 'You see these 23-year-old kids and just the w
arXiv:2608.28113v1 Announce Type: new Abstract: The NVIDIA Blackwell architecture, with native support for the ultra-fine-grained NVFP4 format, opens new opportunities for accelerating large language
arXiv:2608.28158v1 Announce Type: new Abstract: Agentic reinforcement learning (RL) often produces irregular rollout trees with shared histories. Training root-to-leaf trajectories independently recom
arXiv:2506.07188v2 Announce Type: replace Abstract: End-to-end neural networks have become a dominant paradigm in autonomous driving, where reliable deployment requires controllable post-training adap
TL;DR: this paper proposes a method to fix hallucination rates to very low levels or zero by disabling neurons which contribute to hallucination. This discovery has been out for a while now, but it ha
arXiv:2608.27510v1 Announce Type: new Abstract: Transcoder attribution graphs are usually trained to explain why a model assigns high probability to a particular next token. We introduce Concept-Targe
arXiv:2608.28404v1 Announce Type: new Abstract: Video generation for autonomous driving cannot follow the web-scale route: driving data is expensive to collect, bound by privacy requirements, and cann
How fast is the Claude Code plugin ecosystem actually growing? Plugin-touching commit activity grew 8.8x in the six months after the initial launch. Researchers studied 1,926 repositories hosting plug
Hi all, I have recently been experimenting with different LLM set ups and after everyone was raving about how good Qwen 3.8 27b was, I was inspired to try and get it deploying. After some battling wit
arXiv:2608.28482v1 Announce Type: new Abstract: This paper evaluates how reward function choice shapes the performance and behavior of LLM forecasters. We compare five proper scoring rules as training
Trace where your AI budget goes, identify the requests that do not justify their spend, and validate lower-cost alternatives with Arize AX. The post How to reduce LLM costs without sacrificing quality
This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. By now you’ve probably heard about last month’s major AI secur
arXiv:2608.27475v1 Announce Type: cross Abstract: Discovering PDEs in heterogeneous media requires jointly identifying the governing operator and the unknown spatial fields that parameterize it. These
I am the product lead for the training platform at @FireworksAI_HQ . Today the Training API and Fireworks Lab are GA. I won’t walk you through all the features. I want to tell you why teams train with
arXiv:2608.28245v1 Announce Type: cross Abstract: We extend the FLOP (fast learning of order and parents) algorithm recently proposed by Wienobst et al. (2026) from observational to interventional dat
I wrote about how AI agents are starting to spontaneously coordinate in complex (and very risky) ways in the Hugging Face Incident, but also about why we need AIs to reach out to humans more for decis
If you want to understand why I stepped back from AI discourse, the Dwarkesh virality is archetypal of everything wrong with it. Actual cyber security experts have classified the OpenAI and Hugging Fa
arXiv:2608.27502v1 Announce Type: cross Abstract: Ensuring the reliability of deep learning-based image retrieval systems is a software engineering challenge. This paper presents a dual contribution:
arXiv:2402.05098v5 Announce Type: replace Abstract: We study the problem of training diffusion models to sample from a distribution with a given unnormalized density or energy function. We benchmark s
arXiv:2603.18031v2 Announce Type: replace Abstract: Balancing fine-grained local modeling with long-range dependency capture under computational constraints remains a central challenge in sequence mod
arXiv:2608.27760v1 Announce Type: new Abstract: We consider the ability of transformer-based language models (LLMs) to learn what we call k-antilocal languages, i.e., languages that have no mutual inf
arXiv:2608.27791v1 Announce Type: new Abstract: Short-term load forecasting (STLF) provides essential information for numerous applications in modern power systems. However, accurate STLF often relies
arXiv:2608.27501v1 Announce Type: new Abstract: Mathematical reasoning has seen rapid progress in large language models (LLMs), yet existing methods optimize predominantly for final-answer correctness
Interesting paper from Tencent. Tencent trains an agent to manage its own working context, and assigns credit at the level of individual context edits. Long-horizon tasks force a model to retrieve, in
Parody captions on the legendary Risitas interview. The $14k/mo figure is from real reporting on heavy AI power users - the best customers really can be the most expensive ones to serve. He's still su
Introducing wrapture New from Graham Dumpleton (of wrapt, mod_wsgi, and New Relic's Python agent fame), who describes Wrapture as taking the monkeypatching ideas from wrapt and extending them to apply
arXiv:2512.22392v2 Announce Type: replace Abstract: Accurate, up-to-date sidewalk data is essential for building accessible and inclusive pedestrian infrastructure, yet current approaches to data coll
arXiv:2608.27866v1 Announce Type: new Abstract: Achieving virtual agents capable of automating tasks across diverse digital environments remains a pivotal challenge in Embodied AI. While Multimodal La
arXiv:2608.27985v1 Announce Type: new Abstract: Monte Carlo Tree Search (MCTS) and every-visit Monte Carlo (MC) control are usually presented as different methods. MCTS is described in the language of
arXiv:2608.27848v1 Announce Type: cross Abstract: Prosody plays an important role in speech translation, conveying information such as emphasis, emotion, and intent beyond lexical content. However, de