Knowledge catalogue
We benchmark Qwen3.6-35B-A3B on an M5 Max MacBook Pro. Across ten prompt lengths and ten decode contexts, Lily was faster than MLX-LM, averaging 1.23× higher prefill throughput and 1.35× higher decode
We’re introducing Gemini 3.8 Flash ⚡️ built to tackle complex agentic and multi-step tasks with even greater diligence. Our most intelligent workhorse model yet delivers significant improvements in re
arXiv:2609.01271v1 Announce Type: cross Abstract: Agentic software engineering benchmarks are typically summarized by nominal category labels such as 'bug fix' or 'feature implementation,' yet benchma
arXiv:2609.01126v1 Announce Type: new Abstract: Online adaptation can help edge time-series forecasting under distribution drift, but its measured benefit is sensitive to evaluation choices. We study
arXiv:2609.00782v1 Announce Type: new Abstract: Unsupervised feature selection seeks a compact subset of informative features without access to class labels, making feature utility difficult to define
arXiv:2609.01354v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) and standard benchmark evaluation both rely on an automatic verifier that turns a free text answer
I'm planning to upgrade my workstation (linux with 5700X/64GB DDR4) for local inference and pytorch training. I'm trying to decide between: 2× AMD Radeon AI PRO R9700 32GB 2× AMD Radeon PRO W7800 48GB
arXiv:2609.01210v1 Announce Type: cross Abstract: Safety benchmarks for large language models often assess the risk of a user query, although the outcome of question answering depends on whether the r
Years ago I built a server, shelved it after some time, but recently realized I have it sitting there. I'm looking to pop in a Tesla V100 32GB card (with proper cooling). But are the component too old
arXiv:2609.01056v1 Announce Type: new Abstract: Despite the growing use of LLM-powered agents to solve multi-step tasks in complex environments, existing benchmarks rarely test state preservation, per
Not written by AI all mistakes mine. I saw people on the subreddit saying that 3.6 works better without thinking. It made me want to know for certain about which is better, 3.6 or 3.8 for low thinking
ZeroDrift Inc., a startup that automates compliance for artificial intelligence communications, today introduced Guard for Agents, a service that lets developers turn written company policies into enf
arXiv:2608.29705v1 Announce Type: cross Abstract: Feed-forward 3D reconstruction models emit a per-pixel confidence that downstream systems read as a reliability signal. It is trained as a loss weight
arXiv:2608.29461v1 Announce Type: new Abstract: Sandbagging models strategically underperform on evaluations while retaining the capabilities being measured. The evaluations that guide frontier-model
arXiv:2608.28592v1 Announce Type: new Abstract: Large language models (LLMs) achieve high scores on medical knowledge examinations, yet real-world oncology is not a knowledge test--it is a sequence of
arXiv:2608.30817v1 Announce Type: cross Abstract: Geospatial foundation models have emerged as state-of-the-art methods for downstream Earth observation tasks. However, existing pretraining methodolog
arXiv:2608.29005v1 Announce Type: new Abstract: Camera-only end-to-end (E2E) driving models are nearing deployment, where the camera stream is degraded by blur, noise, low light, weather, frame loss,
arXiv:2608.29702v1 Announce Type: new Abstract: A token-embedding table holds a hub of short rows near its origin, and we show that this cluster biases what nearest-neighbor intrinsic-dimension (ID) e
arXiv:2608.31069v1 Announce Type: cross Abstract: Large language models decode by projecting hidden states through a large vocabulary head at every step. This operation is computationally costly and f
arXiv:2512.13392v3 Announce Type: replace Abstract: Disocclusion occurs when object movement reveals previously hidden content. Existing image-to-video methods provide different forms of motion and di
arXiv:2608.30963v1 Announce Type: cross Abstract: Modern large language model (LLM) serving systems increasingly operate over repeated or shared context, yet each model typically performs its own pref
arXiv:2608.28923v1 Announce Type: cross Abstract: Data augmentation is a cornerstone of deep learning pipelines, yet existing strategies treat it as a static, model-agnostic preprocessing step, either
arXiv:2608.30556v1 Announce Type: new Abstract: Path-finding over knowledge graphs has become an effective way to ground LLM reasoning on multi-hop questions. However, biomedical QA introduces two dis
arXiv:2608.29208v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models, built upon Vision-Language Models (VLMs), have significantly enhanced robotic capabilities by leveraging internet
arXiv:2608.28778v1 Announce Type: cross Abstract: Autonomous vehicles (AVs) rely on accurate camera-LiDAR calibration for multimodal sensor fusion. In practice, calibration can drift due to vibration,
Visko Platform Inc., an artificial intelligence research lab focused on developing persistent world models, said today it has raised 10 million in a pre-seed funding round from Llama Ventures. It’s al
arXiv:2601.12449v2 Announce Type: replace-cross Abstract: AI agents are autonomous systems that combine LLMs with external tools to solve complex tasks. While such tools extend capability, improper to
arXiv:2602.02475v2 Announce Type: replace Abstract: AI agents often fail in ways that are difficult to localize because executions are probabilistic, long-horizon, multi-agent, and mediated by noisy t
arXiv:2608.29537v1 Announce Type: cross Abstract: Frozen vision-language-action (VLA) policies offer broad manipulation skills but execute open-loop action chunks without tracking task progress, so th
arXiv:2508.04865v4 Announce Type: replace Abstract: Large language models (LLMs) already excel at writing code in high-resource languages such as Python and JavaScript, yet stumble on low-resource lan
arXiv:2608.29133v1 Announce Type: new Abstract: History is not preserved in complete, continuous form. Accounts of a person's activities, relationships and historical contexts are scattered across tex
arXiv:2502.06584v2 Announce Type: replace Abstract: Early Classification of Time Series (ECTS) is vital in fields like industrial monitoring and medical triage, where quick and accurate predictions ar
arXiv:2608.29397v1 Announce Type: new Abstract: Tool-use benchmarks generally evaluate whether an agent completes a workflow using appropriate tools and valid arguments. However, feasibility alone is
If you are thinking what model will fit best your HW specs and tasks you are doing here is one table with all currently popular models that still can be considered as local. LLM Test Scores Feature De
arXiv:2608.29314v1 Announce Type: new Abstract: We represent lexical tokens as unitary matrices and encode each sentence as their ordered product. The noncommutativity of matrix product captures word
arXiv:2608.30197v1 Announce Type: new Abstract: Safety alignment is essential for deploying large language models, requiring systems to prevent harmful compliance while preserving helpfulness on benig
arXiv:2608.30218v1 Announce Type: new Abstract: Continuous-time 4D reconstruction remains impractical on standalone XR headsets. Per-scene optimization demands deployment-infeasible compute, and lower
arXiv:2608.30702v1 Announce Type: cross Abstract: Large language models are increasingly used as agents for multistep retrosynthesis, raising the question of how much their search policy contributes i
arXiv:2608.29175v1 Announce Type: new Abstract: Temporal inconsistencies, such as mandates attributed outside their real interval, events presented as past before they occurred, or inverted causal seq
arXiv:2608.29973v1 Announce Type: new Abstract: Cryptocurrency markets generate high-frequency, multi-source data that is expensive to work with unless a team already has commercial-grade streaming an
arXiv:2608.31025v1 Announce Type: new Abstract: Inferring object dynamics from visual observations is essential for intelligent agents to reason about and interact with the physical world, yet remains
arXiv:2606.17446v2 Announce Type: replace-cross Abstract: Simulation enables scalable robot data collection, but raw 3D assets provide only geometry, lacking the semantic, interactive, and physical kn
arXiv:2608.30929v1 Announce Type: new Abstract: We present a family of retrieval methods for Polish statutory law built on document surrogates: language-model annotations attached to statutory article
Another Update: in openai, we ARE continuously working on Prism, the scientific/technical writing surface. It is owned by a small team; improvements are coming, although we wish we can ship more. The
Anthropic PBC today debuted Claude Fable 5.1 and Claude Mythos 5.1, its most capable large language models to date. The launch comes a day after the company inked a 35 billion infrastructure deal with
Anthropic says its newest AI models, Fable 5.1 and Mythos 5.1, address criticisms from customers about price, data retention, and overzealous safeguards. The company claims Claude Fable 5.1 offers str
Carl Franzen / VentureBeat: Anthropic says Fable 5.1 sets new standards on coding, knowledge work, and long-running problem-solving tasks, and can fix the root causes of software issues — It's only th
Zac Hall / 9to5Mac: Anthropic says Fable 5.1 will cost an estimated 25% less than Fable 5 for typical workloads and up to 45% less for highly agentic work — In June, Anthropic first released Fable 5,
Anthropic: Anthropic unveils Claude Fable 5.1, which is generally available, and Mythos 5.1, for trusted partners and with cybersecurity and life sciences safeguards — We're introducing Claude Fable 5
arXiv:2608.29242v1 Announce Type: new Abstract: Collecting contact-rich robot experiences at scale remains a major bottleneck for generalizable manipulation. Beyond data quantity, robot learning also
arXiv:2608.29128v1 Announce Type: new Abstract: Tool-using agents are commonly evaluated by a single bit: whether an end-to-end workflow completed. This metric fails to distinguish failures that matte
arXiv:2606.18586v2 Announce Type: replace-cross Abstract: Physical events are not understood by their names alone, but by the causal state changes that compose them. A clip-level label such as 'bounce
arXiv:2606.18613v4 Announce Type: replace-cross Abstract: The most plausible near-term role of medical LLMs is to assist rather than replace physicians, yet current evaluations often test isolated cap
arXiv:2606.15017v2 Announce Type: replace Abstract: Online web agents often augment a base actor with memory, workflow, or skill modules. These modules can improve performance, but they also consume t
arXiv:2608.29529v1 Announce Type: cross Abstract: Semantic alignment between specialized normative texts is challenging when equivalent requirements use different terms, syntax, and levels of abstract
arXiv:2608.30092v1 Announce Type: cross Abstract: We present Arkios, a 1.04B-parameter dense transformer pretrained from scratch on 150B tokens of bilingual English-Nepali text, using a custom single-
arXiv:2608.31111v1 Announce Type: new Abstract: Many important forms of human learning begin with a vague goal, such as 'become a better physicist' or 'improve at research.' Learners must interpret th
arXiv:2608.30372v1 Announce Type: new Abstract: As Large Language Models rapidly advance, performance on standard multiple-choice question answering (MCQA) benchmarks is reaching saturation. While the
arXiv:2608.28945v1 Announce Type: new Abstract: Automating alignment research may accelerate progress toward aligned AI, but whether it does is hard to measure. Luckily, many alignment failures, such
arXiv:2608.30751v1 Announce Type: new Abstract: Large language models (LLMs) trained only on text and code can sometimes generate programs that draw recognizable images. However, it is unclear whether