Knowledge catalogue
OpenAI has released GPT‑5.6 Sol, which powers both instant and deep‑reasoning modes for ChatGPT Plus and Pro customers, delivering fact‑centric responses. Free and Go tier users will receive unlimited
Link to the article: KV Cache Quantization Benchmarks: KVarN, Precision Tail KLD benchmarks with BeeLlama.cpp v0.4.0, fork of llama.cpp with more KV cache quantization options. Models: Qwen 3.6 27B Q5
arXiv:2608.04057v1 Announce Type: cross Abstract: Top-k selection determines which components of a sparse model remain active. Hard selection blocks gradients, while continuous relaxations often coupl
arXiv:2510.21084v3 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown strong potential for clinical decision support through their advanced language understanding and reaso
NVIDIA Nemotron Parse 2.0 transforms document images into structured, machine-readable representations with text, layout classes, bounding boxes, and reading-order information. Given a Red, Green, Blu
arXiv:2608.04434v1 Announce Type: new Abstract: Recent large language models (LLMs) have demonstrated remarkable progress in constraint-aware navigation, maze reasoning, and graph reasoning. However,
arXiv:2608.04575v1 Announce Type: cross Abstract: Reliable physical reasoning from video requires understanding how objects move, interact, and respond to interventions. Existing vision-language model
arXiv:2512.18367v2 Announce Type: replace-cross Abstract: Diffusion models are highly expressive image priors for Bayesian inverse problems. However, most diffusion models cannot operate on large-scal
arXiv:2608.04514v1 Announce Type: new Abstract: Background: Respiratory specialty care requires multimodal interpretation, longitudinal risk assessment, guideline-concordant intervention, and whole-co
arXiv:2608.04480v1 Announce Type: new Abstract: Video temporal grounding (VTG) refers to the task of identifying the time interval in a video that corresponds to a given natural-language query. A comm
arXiv:2608.05018v1 Announce Type: new Abstract: Short-term load forecasting (STLF) play a vital role in the electric power industry. It serves infrastructure that European and German law designate as
arXiv:2608.04043v1 Announce Type: new Abstract: Resistive pressure arrays are the cheapest and most widely shipped tactile sensors, yet tactile representation learning has concentrated on optical sens
arXiv:2608.05136v1 Announce Type: new Abstract: Gradient descent on a factored model W = UV^op is implicitly biased toward low-rank solutions, while Adam, starting from the same small initialization,
This webinar is happening in 30 minutes, and that means there's still time to register! Following the discussion will be an open Q&A with our Head of AI Education @Prof_OZ, and the @arizeai team. See
arXiv:2608.04015v1 Announce Type: new Abstract: With the increase in digitized resources of Classical Latin texts and modern breakthroughs of Large Language Models (LLMs), I contribute to ancient lang
Uber burned through its 2026 AI coding budget in four months. Microsoft canceled most of its Claude Code licenses six months after rolling them out. The mechanics are simple: per-token cost keeps fall
arXiv:2608.03927v1 Announce Type: new Abstract: Engineered Skeletal Muscle Tissues (ESMs) have become a key structure for biomedical disease modeling and pharmacological screening, yet their functiona
https://github.com/mohsinkaleem/agent-mini.git A minimal 3k lines, local-first AI agent you can actually understand and extend. Optimized for smaller local models like qwen 3.6 4b or 9b pip install ag
arXiv:2608.03744v1 Announce Type: new Abstract: Clinical decision support is moving toward committees of language-model agents deliberating on a shared workspace. We ask whether such committees can be
arXiv:2502.11140v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have become a cornerstone for automated visualization code generation, enabling users to create charts through na
arXiv:2601.17003v2 Announce Type: replace-cross Abstract: Mental-health AI safety is typically evaluated with small, simulation-based benchmarks that may not reflect the linguistic and contextual dive
arXiv:2607.11844v2 Announce Type: replace Abstract: Recent Multimodal Large Language Models (MLLMs) achieve strong performance on single-view video understanding benchmarks. However, sports videos inv
Hey everyone, I’ve been building Speechfony - a desktop app for reading PDFs (and EPUBs) with offline text-to-speech. Open a document, listen sentence-by-sentence with highlighting, or export selected
arXiv:2608.03731v1 Announce Type: new Abstract: Patient-facing medical LLMs and agents increasingly answer symptom questions before clinician contact, where the key safety question is what action the
arXiv:2608.03505v1 Announce Type: new Abstract: Constructed languages (conlangs) are intentionally created human languages with a rich tradition of linguistic creativity. Despite their potential for s
Inspired by a post from u/giveen I motivated claude (no patinence on my side to work through everything myself) to help me get DS running on my MacBook M5 Pro 64GB and it exceeded my expectations.. be
arXiv:2608.02990v1 Announce Type: new Abstract: Latent diffusion models (LDMs) have recently significantly advanced embodied learning in constructing powerful embodied manipulation world models. Howev
arXiv:2608.02966v1 Announce Type: new Abstract: Most multiple-choice question (MCQ) benchmarks evaluate Large Language Models (LLMs) only by whether they select the correct answers. This binary scorin
Ivan Mehta / TechCrunch: Hark, founded by Figure AI CEO Brett Adcock, previews Handoff, a computer use agent it says outperforms GPT-5.4 and Opus 4.8, and plans for a summer release — Hark, a startup
arXiv:2603.26468v2 Announce Type: replace Abstract: The rapid growth of hyperspectral data archives in remote sensing (RS) necessitates effective compression methods for storage and transmission. Rece
arXiv:2608.03210v1 Announce Type: new Abstract: Foundation models have achieved remarkable success across diverse tasks, but they remain vulnerable. To investigate such vulnerabilities, semantic-shift
arXiv:2608.02639v1 Announce Type: cross Abstract: Production prompts rarely carry a single instruction. One system message may require valid JSON, a word limit, three citations, and a fixed tone at th
arXiv:2608.03138v1 Announce Type: cross Abstract: Generating a rigorous paper introduction with large language models (LLMs) remains challenging, since it requires coordinating background, gap identif
arXiv:2608.02957v1 Announce Type: new Abstract: Steering vectors (SVs) are widely used to influence the expression of concepts (e.g., truthfulness) in large language model outputs. A key assumption un
arXiv:2608.02621v1 Announce Type: cross Abstract: Legal benchmarks typically score final answers even when models also state legal authority. We test whether answer correctness can serve as a proxy fo
arXiv:2608.02613v1 Announce Type: cross Abstract: Edge-deployed personal memory assistants must handle private interpersonal conversations on-device with open-weight models. Yet, existing memory bench
arXiv:2608.03275v1 Announce Type: new Abstract: Parameter-efficient fine-tuning (PEFT) enables efficient adaptation of large language models, but existing MoE-based PEFT methods typically improve capa
arXiv:2608.03474v1 Announce Type: new Abstract: Recent advances in Large Vision-Language Models (LVLMs) have demonstrated impressive capabilities in web UI generation. However, existing benchmarks pre
arXiv:2608.03708v1 Announce Type: new Abstract: Text-to-image diffusion models enable personalization of specific visual concepts from a small number of reference images. However, generating a single
arXiv:2608.03885v1 Announce Type: new Abstract: Vision-language models exhibit remarkable zero-shot capabilities but suffer significant performance degradation under distribution shifts. While test-ti
arXiv:2608.02844v1 Announce Type: cross Abstract: We develop a class of diffusion-based stochastic particle optimisation methods for loss functions with intractable gradients. Specifically, we conside
arXiv:2608.03682v1 Announce Type: new Abstract: Physical AI policies require inference throughout their lifecycle, including model evaluation, cloud reinforcement learning rollout, edge GPU serving, a
arXiv:2608.03135v1 Announce Type: cross Abstract: Text-to-image diffusion models can generate individual concepts well, but they often omit or merge concepts incorrectly with multiple concepts. We tra
arXiv:2608.02683v1 Announce Type: cross Abstract: Large Language Model (LLM) agents rely on multi-stage agentic workflows, with stages such as memory, planning, and tool execution, to accomplish compl
arXiv:2608.02672v1 Announce Type: cross Abstract: Cloud misconfiguration remains a leading cause of security incidents, yet whether LLMs and SLMs can generate security-compliant Infrastructure-as-Code
arXiv:2509.25459v2 Announce Type: replace Abstract: Large Language Models (LLMs) show promise in generating long-form scientific explanations that synthesize evidence and connect multiple factors. How
Skill libraries are shipping in agent harnesses on the assumption that writing skills down compounds. A new benchmark tests that directly. ContinualSkillBench covers five domains, each with 100 interc
Hear me out before you roll your eyes. We tend to only recognize turning points in hindsight. Nobody in 1993 thought the Mosaic browser would be a history book moment, but the web is. I think Stable D
arXiv:2607.27933v2 Announce Type: replace Abstract: Flow matching (FM) has become a popular action head paradigm for modern embodied models. However, as a conditional generative model, it does not exp
arXiv:2608.03263v1 Announce Type: cross Abstract: We test whether the 'compositional ignition' reported in latent-reasoning models is real computation, an instrument artifact, or inherited from verbal
So I'm looking at https://huggingface.co/unsloth/DeepSeek-V4-Flash-0731-GGUF and I realize my 128GB of DRAM just isn't cutting it for this (incredibly powerful) model. If only I had another 64GB, I th
arXiv:2608.03339v1 Announce Type: new Abstract: Enterprise forecasting increasingly relies on autonomous agents that interpret documents, search for data, generate code, and revise models. While this
arXiv:2608.02680v1 Announce Type: cross Abstract: Tool-using language-model agents repeatedly rediscover procedures they have already executed, producing traces that mix reusable structure with retrie
arXiv:2608.03018v1 Announce Type: new Abstract: Modern cities rely on an increasing number of digital services to operate, but residents' daily needs are still difficult to meet. Services are fragment
arXiv:2608.02878v1 Announce Type: new Abstract: Large language models have shown promise for automated Verilog RTL generation, yet state-of-the-art multi-agent systems plateau at ~95% accuracy on stan
arXiv:2608.03994v1 Announce Type: new Abstract: We identify a previously overlooked failure mode of ALiBi positional encoding: its linear bias scaling underflows floating-point precision, which zeroes
arXiv:2608.04008v1 Announce Type: new Abstract: Benchmarks that measure the forecasting ability of large language models are almost always retrospective: the event has happened, the answer is somewher
arXiv:2608.02657v1 Announce Type: cross Abstract: Agentic LLMs are vulnerable to indirect prompt injection (IPI) attacks, e.g., malicious side-tasks hidden in external tool results. While many efforts
arXiv:2608.00218v1 Announce Type: new Abstract: Agentic LLMs exhibit three consequential tool-use failures: invalid arguments (validity), unnecessary calls (over-calling), and omitted calls when tools
arXiv:2606.15974v2 Announce Type: replace Abstract: Despite the significant advancement of LLMs in conversation summarization, their evaluation remains limited by insufficient scenarios, input lengths