Knowledge catalogue
if you replace billions with millions, this sounds like any other high-growth startup fundraise announcement 😉 We've raised 65 billion in Series H funding at a 965 billion post-money valuation, led by
arXiv:2605.28218v1 Announce Type: new Abstract: Modern translation workflows demand more than semantic equivalence. Users routinely require models to preserve JSON or HTML schemas, honor curated gloss
I'm proud to share that @Glean has surpassed 300M ARR, just five months after crossing 200M and growing ~3x over the past 15 months. This is an exciting milestone for Glean, and it's a signal about wh
arXiv:2605.28736v1 Announce Type: new Abstract: This study presents the first evaluation of general-purpose imitation learning for surgeon-robot collaborative assistance in open surgery, targeting sut
In the last 30 days alone: – Microsoft cancelled most of its Claude Code licenses, citing cost – Uber burned through its entire 2026 AI budget in 4 months – Uber's COO publicly said AI costs are 'hard
arXiv:2605.28324v1 Announce Type: new Abstract: In this paper, we propose a novel conditional diffusion-based framework for multivariable time-series solar power forecasting. The proposed method refor
arXiv:2605.28006v1 Announce Type: cross Abstract: Understanding how LLMs reason is hindered by a practical asymmetry: while their generated outputs are observable, the underlying reasoning patterns re
arXiv:2605.28605v1 Announce Type: new Abstract: Self-supervised low-light image enhancement (LLIE) is highly appealing as it eliminates the reliance on external paired data. However, the lack of exter
arXiv:2605.28649v1 Announce Type: cross Abstract: LLMs increasingly require surgical model editing to enhance domain-specific capabilities without incurring the computational cost or catastrophic forg
arXiv:2605.28714v1 Announce Type: cross Abstract: An Initial Public Offering (IPO) filing is a document released when a private firm goes public, allowing individual (retail) investors to purchase its
arXiv:2605.28247v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a key technique for en- hancing LLM reasoning, yet its data ineffi- ciency remains a
arXiv:2605.28495v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) has emerged as a promising paradigm for Continual Learning. It independently updates its low-rank factors (A and B), creating
arXiv:2601.01627v3 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) are increasingly deployed in healthcare field, it becomes essential to carefully evaluate their medical safety
just noticed today - the dataset is already past 1k+ downloads. opensource / openresearch ftw ! @evo__hq would be opensourcing as many datasets, evals and autoresearch runs as we can in our pursuit of
arXiv:2605.28013v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) exacerbate safety risks by introducing vulnerabilities across multiple modalities, such as language and vision.
arXiv:2605.27984v1 Announce Type: cross Abstract: Speech language models (SpeechLMs) have achieved substantial progress by extending large language models (LLMs) to the speech modality. However, Speec
arXiv:2605.27605v1 Announce Type: new Abstract: We present Laguna M.1 and Laguna XS.2, two Mixture-of-Experts foundation models built for long-horizon, agentic coding: M.1 has 225.8B total parameters
arXiv:2605.27989v1 Announce Type: new Abstract: The guidance of scaling laws has increased the resource demands of modern large language models (LLMs), yet it remains questionable whether these models
arXiv:2605.27375v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly acting as autonomous agents, but their continuous interaction with the environment can lead to in-context
arXiv:2605.28007v1 Announce Type: cross Abstract: Deep networks are powerful function approximators, but they typically store many different computations in shared weight matrices, making it difficult
arXiv:2605.27642v1 Announce Type: new Abstract: Soft prompt tuning is a parameter-efficient method for adapting LLMs to specific tasks, but suffers from a lack of interpretability. Building on recent
arXiv:2605.28368v1 Announce Type: new Abstract: World models have enabled interactive exploration of game environments and robotic manipulation, but physical engineering remains beyond their reach: re
arXiv:2602.20497v3 Announce Type: replace-cross Abstract: Diffusion models have achieved remarkable success in image and video generation tasks. However, the high computational demands of Diffusion Tr
arXiv:2605.27914v1 Announce Type: cross Abstract: Subjective evaluation of LLM behavior -- empathy, restraint, calibrated emotional tone -- is hard. Human inter-rater agreement on such qualities satur
arXiv:2605.28721v1 Announce Type: new Abstract: Are LLM-based search agents genuinely searching, or using the web to verify what they already know? We study this question on BrowseComp with three diag
Release: llm-anthropic 0.25.1 New model: Claude Opus 4.8 (claude-opus-4.8). New -o fast 1 option for fast mode, for organizations with that feature enabled on their account. Default max_tokens for eac
arXiv:2605.28760v1 Announce Type: new Abstract: Zeroth-order (ZO) fine-tuning is attractive for large language models because it replaces backpropagation with forward objective evaluations. Existing i
arXiv:2506.08928v2 Announce Type: replace Abstract: Tree-based ensembles such as random forests remain the go-to for tabular data over deep learning models due to their prediction performance and comp
Local Reachy Mini conversations wireless looks like magic! You can bring your friend around the house and get WOW effect from anyone! 🔥 Thanks @andimarafioti for the blog post on how to set this up: h
arXiv:2605.28271v1 Announce Type: new Abstract: Object detection is an important task in computer vision, which aims to detect the objects of interest. through the given category list or query images.
arXiv:2605.28077v1 Announce Type: new Abstract: Parsing chemical reaction diagrams from scientific literature is challenging due to heterogeneous layouts, intertwined visual elements, and the difficul
arXiv:2605.27960v1 Announce Type: new Abstract: Despite their popularity and success, Multimodal Large Language Models (MLLMs) often struggle to interpret images accurately, which limits their reasoni
arXiv:2605.27748v1 Announce Type: cross Abstract: Industrial visual anomaly detection is usually one-class: normal images are abundant, while defects are rare, heterogeneous, and often unavailable dur
arXiv:2605.28173v1 Announce Type: new Abstract: End-to-end manga generation is a structured visual storytelling task that requires story decomposition, recurring character and scene grounding, page la
arXiv:2603.21165v2 Announce Type: replace Abstract: Bangla culture is richly expressed through region, dialect, history, food, politics, media, and everyday visual life, yet it remains underrepresente
Tool: markdown-svg-renderer A slightly customized Markdown rendering tool with special treatment for fenced code SVG blocks - it both renders the image and provides a tab for switching to the code vie
arXiv:2605.28646v1 Announce Type: cross Abstract: GUI agents rely on screenshots to infer intent and operate across applications, but these screenshots often contain private messages, medical records,
arXiv:2605.28046v1 Announce Type: new Abstract: Existing agent memory systems universally follow what we term a Memory-as-Tool paradigm where a single query triggers one-shot retrieval of flat passage
arXiv:2605.28009v1 Announce Type: cross Abstract: Memory-augmented large language models extend reasoning beyond a fixed context window by maintaining long-term memory across interactions. However, ex
arXiv:2605.28732v1 Announce Type: cross Abstract: Memory is essential for enabling large language models to support long-horizon reasoning, yet existing memory systems remain unreliable and difficult
arXiv:2605.28161v1 Announce Type: new Abstract: Clinical diagnosis of meniscus injuries requires radiologists to integrate volumetric MRI evidence with patient context (e.g., sex, age, BMI) and to pro
arXiv:2605.28384v1 Announce Type: new Abstract: Standard transformer architectures apply a single attention mechanism uniformly across all tokens and sequence positions, irrespective of local context
arXiv:2510.01724v2 Announce Type: replace Abstract: Mass spectrometry-based metabolomics generates complex, high-dimensional data that holds vast potential for biological discovery but remains difficu
arXiv:2605.28025v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to provide public-facing health information, yet existing safety evaluations overlook whether respons
arXiv:2605.28116v1 Announce Type: cross Abstract: Mobile graphical user interface (GUI) agents driven by vision-language models (VLMs) perceive the screen as rendered pixels and choose actions from wh
Sam Schechner / Wall Street Journal: Mistral says it is accelerating superintelligence development to ensure Europe's independence from US tech giants, and signs deals to supply Airbus and BMW — Frenc
arXiv:2602.03515v2 Announce Type: replace-cross Abstract: Asynchronous pipeline parallelism maximizes hardware utilization by eliminating the pipeline bubbles inherent in synchronous execution, offeri
arXiv:2505.21771v2 Announce Type: replace-cross Abstract: Multimodal tables i.e. tabular layouts interleaved with charts, maps, icons, and color encodings are ubiquitous in real applications yet remai
arXiv:2605.28591v1 Announce Type: cross Abstract: The validity of AI safety evaluations depends on models behaving consistently across controlled and deployment settings. Prior work has identified tes
arXiv:2605.27853v1 Announce Type: new Abstract: We present MolLingo, a multi-agent system that emulates the reasoning process of a chemist to automate molecular design. Existing LLM-based approaches e
arXiv:2602.23602v2 Announce Type: replace-cross Abstract: Heteroscedasticity -- where the variance of a variable changes with other variables -- is pervasive in real data, and elucidating why it arise
arXiv:2605.28035v1 Announce Type: new Abstract: In recent years, Multi-Talker Audio-Video Generation (MTAVG) models have shown promising performance on fundamental metrics such as lip-sync and audio-v
arXiv:2605.28722v1 Announce Type: new Abstract: Representation intervention has emerged as a promising paradigm for aligning large language models toward desired behaviors without modifying model weig
arXiv:2605.28579v1 Announce Type: new Abstract: Large language models (LLMs) have recently advanced text-driven 3D generation, yet Text-to-CAD remains far from supporting industrial product design. Ex
Organizations are unlocking entirely new ways to use image generation and editing across their industries. To drive next-generation experiences, businesses are embedding AI directly into creative, age
arXiv:2603.12824v2 Announce Type: replace-cross Abstract: Vision-Language Model (VLM) based retrievers have advanced visual document retrieval (VDR) to impressive quality. They require the same multi-
New in Claude Code (research preview): dynamic workflows. Claude writes an orchestration script on the fly, then spins up a large fleet of coordinated subagents in parallel to take on your most comple
arXiv:2605.27454v1 Announce Type: cross Abstract: X-ray computed tomography (XCT) is widely used for non-destructive testing of Nomex honeycomb structures in aerospace manufacturing, but industrial in
arXiv:2511.18894v5 Announce Type: replace-cross Abstract: Medical image segmentation is crucial for clinical applications, but it is frequently disrupted by noisy annotations and ambiguous anatomical
arXiv:2605.28168v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated promising capability in generating reward functions for deep reinforcement learning (DRL)-based building