Search: “reasoning”

I am writing a fairly complex C++ windows MFC application. I have a few 3090s and can run F16 Qwen3.6-27B with 256K context and MTP. The quality of code is exceptional with this quant vs its lower qua

Last week someone here said ThinkingCap and Fable Fusion 'really do beat the OG' for agentic work, so I ran it: 6 self-grading tasks, 5 reps, 3 models, 90 isolated runs. Tooling, since that's half the

BREAKING: A Redditor just discovered that shared Claude conversations have been showing up in public search results. The post has 4K upvotes and hundreds of comments, so this is spreading fast. Here's

I ran DeepSeek V4 Flash through Claude Code, OpenCode and Pi on my own benchmark, and the quality came out basically the same across all three while the time and tokens spent was wildly different. Cla

Qwen3.6-27B: SFT vs continued pre-training vs RL? I’m interested in adapting Qwen3.6-27B, but I’m increasingly unsure whether conventional SFT/LoRA is the best route if the goal is to add a capability

Simply untrue. The Economist asked Musk about a wide range of things, including AI and robotics. Watch it here for yourself: https://www.economist.com/insider/the-insider/an-interview-with-elon-musk?u

Anthropic PBC today rolled out a large language model called Claude Opus 5 to its chatbot service and developer platform. The company says the LLM approaches the output quality of its top-end Mythos 5

Cuda and Vulkan Benchmark: TensorSharp vs. llama.cpp I would like to share my latest open source local Unsloth (GGUF) LLM inference engine and applications. It supports many models from Unsloth, like

Diffusion LLMs can now handle real agentic work. LLaDA 2.2 is the first large-scale diffusion LLM built to operate as a real agent, planning, calling tools, and self-correcting across long multi-turn

RTX 4070, 32gb system ram, Linux. NVIDIA-SMI 610.43.03, KMD Version: 610.43.03, CUDA UMD Version: 13.3 Systemd service modifications: [Service] Environment='OLLAMA_HOST=0.0.0.0:11434' Environment='OLL

Very happy to support this on behalf of Google. We have long benefited from open source, are big contributors to open source and in fact have consistently made open weights models with Gemma available

arXiv:2607.20535v1 Announce Type: cross Abstract: Traditional Predictive Digital Twins often remain geometrically rigid, requiring extensive retraining or fine-tuning whenever the underlying physical

arXiv:2607.21057v1 Announce Type: new Abstract: Text-based person retrieval faces a critical but under-explored challenge: the inherent uncertainty of query granularity in real-world scenarios. This p

arXiv:2607.21437v1 Announce Type: new Abstract: Deep learning models can effectively use Rapid Evaporative Ionization Mass Spectrometry (REIMS) data for surgical margin assessment. However, their clin

arXiv:2607.20498v1 Announce Type: new Abstract: Large language models (LLMs) augmented with tools are emerging as autonomous agents capable of using Web engine, APIs, and code to solve complex, long-h

Am I supposed to interpret that it's better than Fable 5 from the benchmarks? Or it's ~close but cheaper? Introducing Claude Opus 5. It's a thoughtful and proactive model that comes close to the front

As AI moves beyond chatbots toward autonomous agents, attention is shifting enterprise AI PCs as a new layer of AI infrastructure. That transition is driving demand for hardware and software designed

arXiv:2607.21424v1 Announce Type: new Abstract: Recent advancements in automated audio captioning (AAC) have shifted from monolithic sentence generation toward structured formats that explicitly disen

Announcing Fugu-Ultra v1.1 🐡 We’ve been thrilled by the reception to the Fugu model family. Thanks to everyone who tried it, shared feedback, and trusted Fugu with real work. Today, we’re releasing Fu

arXiv:2607.20764v1 Announce Type: new Abstract: We introduce ARBIGRAPH, a benchmark generator for evaluating whether tool-assisted language agents can retain, update, compose, and discard task-relevan

arXiv:2607.21461v1 Announce Type: new Abstract: Deep research requires agents to find answers that jointly satisfy multiple constraints. Discovering such answers is costly, whereas verifying a candida

arXiv:2607.21106v1 Announce Type: new Abstract: Effective memory is crucial for LLM agents, yet constructing it effectively remains challenging. A memory-construction policy decides what information t

arXiv:2607.21173v1 Announce Type: new Abstract: While automated research systems promise to accelerate empirical analysis, they are prone to silent failures: instances in which analysis code executes

arXiv:2607.20525v1 Announce Type: new Abstract: OpenAI's recent disproof of the Erdos unit distance conjecture marked a milestone for AI in mathematics. It also inspired another breakthrough: a human

arXiv:2607.20488v1 Announce Type: new Abstract: Multi-agent LLM frameworks typically fix their team topology at boot time. When an individual agent becomes overloaded at runtime, for example by mixing

arXiv:2607.20660v1 Announce Type: new Abstract: Recent 3D generative models produce high-quality geometry from a single image using large-scale priors and diffusion architectures. However, they assume

https://reddit.com/link/1v5rvuq/video/bgmwc754i9fh1/player My goal was to create a benchmark to measure the spatial awareness and memory of models. Eventually, I came up with the simple idea of a maze

arXiv:2607.20461v1 Announce Type: cross Abstract: Present implementations of artificial intelligence (AI) ethics do not adequately take feelings, or affect, into account. If AI should be aligned with

arXiv:2607.21340v1 Announce Type: new Abstract: In capital-markets workflows the question is rarely whether a large language model can produce a fluent draft, but whether the draft is bankable: defens

arXiv:2607.21409v1 Announce Type: cross Abstract: A central challenge in quantum machine learning is understanding the scaling behavior of parameterized quantum circuits (PQCs). In particular, it rema

arXiv:2505.18672v2 Announce Type: replace Abstract: Representation intervention aims to localize and modify the representations that encode the underlying concepts in large language models (LLMs) to e

arXiv:2607.21016v1 Announce Type: new Abstract: Culture is lived through conversation, yet existing Indonesian cultural commonsense benchmarks evaluate LLMs on short and isolated prompts, stripping aw

arXiv:2607.20491v1 Announce Type: new Abstract: Standard evaluation benchmarks measure what a tool-using agent decides, not whether it arrives at that decision through the same process each time. We i

arXiv:2607.20675v1 Announce Type: new Abstract: Machine learning (ML) models are increasingly integrated into optical network automation frameworks to support tasks such as failure management, perform

In a previous post (https://www.reddit.com/r/LocalLLaMA/comments/1utefpr/running_qwen3_30b_a3b_at_50_toks_on_rtx_5060_ti/) there seemed to be great demand for bringing in Qwen3.5 35B. Some Gated Delta

https://github.com/shootthesound/Fizgig Intelligent trainer - Per-image loss tracking with self-adapting training runs — every image gets its own verdict (easy / suspect / stuck / exhausted) and its o

For my first post, I’m sharing a letter @NVIDIA signed on why open models matter. AI will transform every industry, power every company, and be built by every country. Open models strengthen safety an

arXiv:2607.21036v1 Announce Type: new Abstract: Adversarial attacks against large vision-language models (LVLMs) serve as an effective means of assessing their robustness in cross-modal semantic under

arXiv:2607.21202v1 Announce Type: cross Abstract: Hybrid MKNF knowledge bases under the well-founded semantics integrate Description Logics with Logic Programming. However, they do not support classic

arXiv:2607.20988v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models augmented with world modeling represent a promising paradigm for end-to-end autonomous driving. While pixel-level

arXiv:2604.01925v2 Announce Type: replace-cross Abstract: Large Language Models increasingly suppress biased outputs when demographic identity is stated explicitly, yet may still exhibit implicit bias

arXiv:2607.20427v1 Announce Type: cross Abstract: Mixture-of-Experts architectures have revolutionized scaling, yet the underlying logic of their routing remains a black box. In this paper, we uncover

arXiv:2607.20456v1 Announce Type: cross Abstract: Large language models excel at code generation for mainstream programming languages but struggle with rare, domain-specific languages such as MiniZinc

arXiv:2607.20690v1 Announce Type: new Abstract: Small language models and coding agents increasingly generate web front-end code, yet their outputs are typically evaluated primarily for functional cor

arXiv:2607.20924v1 Announce Type: new Abstract: Makeup-transfer applies the reference makeup to the source face while preserving the source identity. Despite advances in full-face editing by diffusion

arXiv:2607.20433v1 Announce Type: cross Abstract: While language models remain frozen at their training state, the world evolves continuously. Knowledge editing has emerged as a key alternative to ful