Knowledge catalogue
arXiv:2608.29247v1 Announce Type: new Abstract: Deep neural networks remain highly vulnerable to adversarial perturbations, and adversarial training (AT) has become a widely used approach for improvin
arXiv:2608.30307v1 Announce Type: cross Abstract: Text-driven 3D indoor scene generation has advanced from dataset-bound layout modeling to open-vocabulary synthesis with large language and vision-lan
arXiv:2608.30399v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit strong semantic reasoning and open-ended generation abilities, but aligning these abilities with structured seque
arXiv:2608.29270v1 Announce Type: cross Abstract: Autoformalization translates informal mathematical theorems into code for proof assistants such as Lean. A central challenge is that current evaluatio
arXiv:2608.29607v1 Announce Type: new Abstract: Mobile AI acts as a visual oracle, empowering users to snap a picture of something and ask for information. Snap-and-ask retrieval is now one of the mos
arXiv:2512.16956v3 Announce Type: replace-cross Abstract: Retrieving code functions, classes or files relevant to a user query, bug report or feature request from large codebases is a fundamental chal
arXiv:2608.31108v1 Announce Type: new Abstract: Efficient evaluation changes the protocol used to support claims about model behavior, yet it is rarely tested whether those claims remain stable after
arXiv:2608.30068v1 Announce Type: new Abstract: Films communicate through deliberate creative choices, including lighting, color, composition, editing, dialogue, music, and sound. Humans naturally int
arXiv:2608.28660v1 Announce Type: cross Abstract: Test-time scaling (TTS) improves language model reasoning by allocating additional test-time compute, but prior work mainly studies closed-ended tasks
arXiv:2601.08747v3 Announce Type: replace-cross Abstract: Current context augmentation methods, such as retrieval-augmented generation, play a crucial role in bridging a model's internal knowledge bou
As generative AI adoption scales, cost governance becomes a top challenge. Learn how Jamf built real-time, per-user spend enforcement for Amazon Bedrock using IAM Customer Managed Policies, an Amazon
Replit now offers a Multi‑Chat Protocol (MCP) integration that lets users access Replit directly from messaging platforms such as ChatGPT, Claude, Slack, or any other MCP client. The feature and its s
arXiv:2608.30846v1 Announce Type: new Abstract: Fairness audits in clinical Artificial Intelligence convert continuous fairness metrics into binary pass-or-fail verdicts against operational thresholds
arXiv:2608.30819v1 Announce Type: new Abstract: Training autonomous driving policies through pure self-play has recently shown promising results. Following Gigaflow and Puffer- Drive, we train driving
arXiv:2608.31118v1 Announce Type: new Abstract: The effect of Large Language Model (LLM) scale on ontology learning (OL) performance remains insufficiently characterized. We present a controlled evalu
arXiv:2608.30649v1 Announce Type: new Abstract: Removing a specific individual's information from multimodal large language models (MLLMs) is often needed after deployment, but existing methods rely o
arXiv:2608.28407v1 Announce Type: new Abstract: Multi-trait Automated Essay Scoring (AES) requires rubric-grounded reasoning across interdependent traits, rather than isolated score prediction. Existi
We're excited to share that AWS has been recognized as a Leader in The Forrester Wave: AI Infrastructure Solutions, Q4 2025. In this evaluation of 13 providers, AWS received the highest score in the S
arXiv:2608.28394v1 Announce Type: cross Abstract: Cyber threat intelligence (CTI) is foundational to modern cyber defense, yet much of it resides in unstructured reports whose volume and heterogeneity
arXiv:2608.27893v1 Announce Type: new Abstract: High-quality e-commerce creatives are essential for presenting products and conveying marketing messages. Recent diffusion models enable scalable creati
arXiv:2608.28405v1 Announce Type: new Abstract: Current cultural evaluations for large language models (LLMs) often reduce culture to single-turn factual recall via MCQs, failing to capture a common u
I'm very happy with Qwen-3.8-27B, I run it on my work machine and switched for major part of real coding tasks from cloud subscriptions to it. I use one dedicated headless RTX 3090, and get maybe 1000
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
“it’s stuff like this that really makes me roll my eyes … Does everyone have psychosis or losing critical thinking ability? …. OpenAI’s…. IT team can’t be this bad… this is like 101 stuff … 2. Civiliz
Just WOW! Absolutely unacceptable. I look forward to understanding how that is possible. LLM tools get going and you can’t be 100% certain what they’re gonna do. Just like any LLM, you can ask coding
arXiv:2511.23271v2 Announce Type: replace Abstract: Long system prompts are widely used to steer Large Language Models (LLMs), but repeatedly processing them at inference time is inefficient and consu
The LWiAI Podcast #255 (August 26 2026) reviewed recent AI alerts, including Google’s Gemini 3.7 Flash, Jalapeño’s record‑speed benchmark results, Qwen 3.8, and a case of an entirely AI‑guided drone t
arXiv:2608.27923v1 Announce Type: new Abstract: Printed circuit boards (PCBs) are fundamental to modern electronic systems, yet AI-driven PCB design automation remains constrained by the lack of large
arXiv:2608.28406v1 Announce Type: new Abstract: Human mistakes are inevitable when following instructions, yet they can lead to severe consequences. As such, there has been an increased interest in de
11/ METR and Redwood’s work is extremely valuable, but it assesses model behavior and alignment. That is only half the picture. We also need an independent account of how OpenAI’s containment failed.
Hi All, I am currently contemplating an upgrade from my 5060ti 16gb. I am getting ~40t/s with 130k context on Qwen 3.8 IQ3_S HF quant. I am running llama.cpp on linux. Objective is to increase context
I see that you did, @dwarkesh_sp, and thank you for pointing it out. You're absolutely right to highlight the very real dangers of loss of control. I also agree that easy-to-understand language can be
Most neoclouds exhibit weak security controls, exposing users to risks such as container escapes, kernel bypasses, compromised network policies, insecure credential handling, and multi‑tenant Grafana
I have been using the unsloth/Qwen3.8-27B-NVFP4 with 157k ctx on vllm currently. But recently I have been seeing post about ninfer lately and how it is like the best way to run qwen 3.8 on RTX 5090 32
People who moved from older version to this new one, how much improvements do you see on inference? Ex: llama.cpp performance? This new version comes with Linux Kernel 7.0. Hope AMD cards gonna enjoy
~20–30GB smaller than Unsloth/AesSedai Q4 at similar PPL. After several days of testing I released a set of mainline-compatible imatrix quants for Qwen3.8-Flash-Next. Goal: same quality band as the po
arXiv:2608.26177v1 Announce Type: cross Abstract: Long-form generation exposes fundamental limitations of large language models. Even 70B-parameter models exhibit length collapse at 16k-token outputs,
arXiv:2608.26306v1 Announce Type: new Abstract: A large language model (LLM) guardrail for a self-adaptive system (SAS) may issue an approval that is correct at check time but stale by actuation. This
arXiv:2608.26592v1 Announce Type: new Abstract: Following clinical decision pathways (CDPs) defined by clinical practice guidelines is essential for safe and reliable medical decision-making. However,
arXiv:2608.26143v1 Announce Type: cross Abstract: Memes have turned out to be a powerful tool through which individuals share their ideas concerning contemporary social and political problems. Their a
arXiv:2608.26414v1 Announce Type: new Abstract: Medical guidelines encode rich, evidence-based decision logic, yet the specific decision artifact a clinician needs is hard to locate within a guideline
arXiv:2608.26899v1 Announce Type: new Abstract: Automated candidate-job matching systems are increasingly classified as high-risk AI under emerging regulation, yet auditing them for demographic bias i
arXiv:2608.26757v1 Announce Type: new Abstract: Faithful chart generation in real-world data-science workflows requires grounding visualizations in scattered evidence, computing chart-ready quantities
arXiv:2608.26172v1 Announce Type: cross Abstract: Deploying natural-language interfaces over enterprise OLTP catalogs fails at scale because semantic parsers collapse under schema-graph scaling, infla
arXiv:2608.26118v1 Announce Type: new Abstract: Existing long-form factuality evaluation relies on the decompose-retrieve-verify pipeline. However, the pipeline suffers from noise from claim decomposi
arXiv:2608.26151v1 Announce Type: new Abstract: Subscriber attrition is a costly, persistent challenge for telecommunications providers, with monthly churn of roughly 1.9% in mature markets eroding bi
arXiv:2608.26961v1 Announce Type: new Abstract: Graphs are invariant under node permutations, motivating the use of permutation-equivariant architectures in generative models. In flow matching, howeve
I fine-tuned and published SaphraFgt 1.0, an 8B coding model focused on HTML, CSS, JavaScript, frontend development, UI/UX, code completion and debugging. Ollama: [https://ollama.com/SaphraFgt/saphraf
i'm gonna get shredded to pieces like tibo and jarred when they see what i actually look like now... i'll be speaking at the 2nd edition of @aiDotEngineer paris on sep 24th 🇫🇷 i'll be talking about: •
arXiv:2608.26111v1 Announce Type: new Abstract: Battery Prognostics and Health Management (BPHM) is critical for ensuring the safe, reliable, and cost-effective operation of batteries across electric
arXiv:2510.06270v2 Announce Type: replace-cross Abstract: Multi-objective discrete optimization problems, such as molecular design, pose significant challenges due to their vast and unstructured combi
arXiv:2510.18383v4 Announce Type: replace-cross Abstract: Distilling the tool-use capabilities of large language models (LLMs) into small language models (SLMs) is essential for their practical applic
arXiv:2608.26124v1 Announce Type: new Abstract: Pricing automation in large-scale tourism is challenging because travel orders are highly unstructured, while pricing policies are complex, rapidly evol
Now live (and free) at Marcus on AI: takeways on the OpenAI / Hugging Face attack, coauthored with @ZackKorman, focusing not so much on what the AI did as on what OpenAI should have done. https://gary
arXiv:2608.26142v1 Announce Type: cross Abstract: Referring Expression Segmentation (RES) aims to generate pixel-wise segmentation masks from complex and implicit textual queries. While recent advance
TL;DR: Self-learning needs governance, observability, and auditability. Sounds great, it's not great unless you have serious and appropriate protections. Let me lead this off with what we are most pro
arXiv:2606.18801v2 Announce Type: replace-cross Abstract: With the rapid expansion of massive multilingual corpora, Multilingual Information Retrieval (MLIR) has emerged as a critical technology for g
arXiv:2608.26410v1 Announce Type: cross Abstract: Recent work in fair division has focused on either simultaneously satisfying closely related fairness notions or achieving a single notion across the
arXiv:2608.26132v1 Announce Type: cross Abstract: Labeled property graphs combine relational structure with heterogeneous textual and categorical properties attached to both nodes and relationships. C
arXiv:2608.26214v1 Announce Type: new Abstract: Surgical video data provides the primary training resource for models of intraoperative perception, surgical workflow understanding, and robotic decisio