News / #rag Tag Rag 500 articles archived under #rag · RSS Sign in to follow r/LocalLLaMA community 8d ago EmbeddingGemma 2 is a best-in-class open model for natively multimodal embeddings   submitted by   /u/sn2006gy [link]   [comments] 10 r/LocalLLaMA community 8d ago Introducing EmbeddingGemma 2: A best-in-class open model for natively multimodal embeddings | Google https://huggingface.co/google/embeddinggemma-2 EmbeddingGemma 2 is an open multimodal embedding model built by Google DeepMind which maps text (incl. code), images, video, and audio inputs—and combinations thereof—into a single, unified 768-dimensional vector space. The model… 9 llama.cpp releases dev-tools 8d ago b11452 model: support embeddinggemma2 (text+vision+audio) ( #30054 ) 4 r/LocalLLaMA community 8d ago EmbeddingGemma 2 running locally in-browser on WebGPU Model: https://huggingface.co/google/embeddinggemma-2 Demo: https://huggingface.co/spaces/webml-community/embeddinggemma-2-webgpu   submitted by   /u/xenovatech [link]   [comments] 6 r/LocalLLaMA community 8d ago 54gb vram for 35$ Bought an old mining farm of a guy on avito (Russian eBay), guy had bought a garage a couple of years ago and it was sitting there for a while, found out it was a mining farm and put it up on there for sale for 5000 rub (~60 USD) since he wasn't sure if it works. I negotiated… 10 Hacker News — AI on Front Page community 8d ago EmbeddingGemma 2: An open, lightweight multimodal embedding model Article URL: https://blog.google/innovation-and-ai/technology/developers-tools/embeddinggemma-2/ Comments URL: https://news.ycombinator.com/item?id=49980487 Points: 301 # Comments: 31 31 r/LocalLLaMA community 8d ago google/embeddinggemma-2 · Hugging Face EmbeddingGemma 2 is an open multimodal embedding model built by Google DeepMind which maps text (incl. code), images, video, and audio inputs—and combinations thereof—into a single, unified 768-dimensional vector space. The model has 740M total parameters, combining a 270M… 18 llama.cpp releases dev-tools 8d ago b11436: ggml-openvino: fix CI tests; fix GPU regressions. (#30037) ggml-openvino: skip unselected graph branches and support DUP Upstream #29622 adds a mixed token/embd branch to every input embedding graph through ggml_build_forward_select(). Its nodes are not flagged for compute, but the backend translated them anyway, and the DUP in that… 33 r/MachineLearning community 8d ago Embedding Every Font with Neural Networks makes some Nice Structures (including a flower) [P] I've been working on a font searching tool for about a year now, and my investigations have centered around pre-training neural networks to produce embeddings of each font. I usually then need to post-train the networks to adapt them to the task of font searching. However, the… 33 Ars Technica — AI news-outlet 9d ago Command-line tool quickly removes Apple Intelligence from macOS 27 The tool can free up over 12GB of storage. 8 llama.cpp releases dev-tools 9d ago v0.6.0 Overview llama.cpp v0.6.0 introduces the new llama_batch_ext extended batch API (with llama_process ) for mixed token/embedding inputs and MTP/deepstack state embeddings, adds support for the GLM-5.3-Flash (GLM5-Next) 320B hybrid model, the Clef decision model (text and vision)… 27 The Information — AI news-outlet 9d ago What’s Wrong With AI Safety Testing, and How to Fix It The idea that Anthropic , OpenAI and other AI companies could “embed” researchers from outside safety groups into their operations has been all the rage in recent weeks. But the devil is in the details. AI safety researchers worry that embedded evaluators won’t have the access… 7 arXiv — Machine Learning research 9d ago Drive vs. Decay: On the Training Dynamics of Joint-Embedding Predictive Architectures arXiv:2610.02344v1 Announce Type: new Abstract: Joint-Embedding Predictive Architectures (JEPAs) are prone to representation collapse, typically mitigated through empirical heuristics. We develop an early-training stability theory that unifies these heuristics. Linearising the… 21 arXiv — Machine Learning research 9d ago Efficient Neural Field Learning via Adaptive Coverage and Focused Sampling arXiv:2610.02410v1 Announce Type: new Abstract: Implicit neural representations (INRs) provide a flexible framework for modeling high-dimensional continuous fields, but their training is often inefficient due to uniform subsampling that ignores spatial heterogeneity. Existing… 8 arXiv — Machine Learning research 9d ago BaCP: Backbone Contrastive Pruning for Preserving Representations in Extremely Sparse Neural Networks arXiv:2610.02524v1 Announce Type: new Abstract: Unstructured pruning at extreme sparsity often suffers from representational collapse, causing sharp drops in accuracy. To address this, we study Backbone Contrastive Pruning (BaCP), which regularizes the sparse network's embedding… 28 arXiv — Machine Learning research 9d ago Activation Sparsity with Weight Approximation for Faster LLM Decoding on Offloaded Weights arXiv:2610.02598v1 Announce Type: new Abstract: Deploying LLMs on consumer-grade GPUs with insufficient memory to hold their weights can result in prohibitively slow inference, because decoding repeatedly transfers offloaded weights from system RAM or flash storage into GPU at… 32 arXiv — Machine Learning research 9d ago Quantifying the Value of Constructive Induction, Knowledge, and Noise Filtering on Inductive Learning arXiv:2610.02615v1 Announce Type: new Abstract: Learning research, as one of its central goals, tries to measure, model, and understand how learning-problem properties affect average-case learning performance. For example, we would like to quantify the value of constructive… 5 arXiv — Machine Learning research 9d ago MuonIO: Principled Norm-Aware Descent for Embedding Tables and Language Model Heads arXiv:2610.02705v1 Announce Type: new Abstract: The Muon optimizer derives its update rule for hidden linear layers by solving a local linearization of the loss penalized by the spectral norm, motivated by an RMS-stability argument for dense linear layers. Standard Muon… 8 arXiv — Machine Learning research 9d ago Inner Momentum for Differentially Private Muon arXiv:2610.02738v1 Announce Type: new Abstract: Differentially private training clips each per-example gradient before adding noise. This clipping is radial for each example, yet unequal clipping factors can distort the relative singular-vector geometry of their average. Muon is… 29 arXiv — Machine Learning research 9d ago Exact Memory-Time Optimization for Prefix-Cached Language Model Serving arXiv:2610.02766v1 Announce Type: new Abstract: Retaining language-model prefix states trades recomputation against storage time. Optimizing each cached block independently can overcount savings: a resident block is usable only when the required preceding prefix is also… 31 arXiv — NLP / Computation & Language research 9d ago CUEing User Simulators: Calibrated User Embeddings for Multi-Turn Benchmarking arXiv:2610.02460v1 Announce Type: new Abstract: Recent benchmarks rely on user simulators to evaluate AI agents in multi-turn interaction. While existing simulation techniques demonstrate surface fidelity to human style and behavior, ecologically valid interactive benchmarking… 12 arXiv — NLP / Computation & Language research 9d ago Output Language Confusion under Multilingual Prompt Contamination arXiv:2610.02926v1 Announce Type: new Abstract: Standard factual benchmarks assume clean monolingual prompts and exact-match scoring, two assumptions that break simultaneously in real-world multilingual deployment, from retrieval-augmented generation pipelines returning… 36 arXiv — NLP / Computation & Language research 9d ago Investigating the Role of Reasoning-Language Alignment in Monolingual Retrieval-Augmented Generation arXiv:2610.03136v1 Announce Type: new Abstract: Reasoning traces improve large language models (LLMs), but current models are trained to reason mostly in English. It has been shown that forcing a model to reason in another language degrades accuracy, even when the reasoning… 28 arXiv — NLP / Computation & Language research 9d ago CLIMB: Confidence-Guided Complementary Evidence for Multimodal Retrieval-Augmented Generation arXiv:2610.03421v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have shown strong visual reasoning abilities, but knowledge-intensive visual question answering often requires external textual evidence beyond the image and the model's parametric… 17 arXiv — NLP / Computation & Language research 9d ago Author Representation Strategies for Zero-Shot Authorship Attribution: A Comparative Study of LLM-Based and Embedding-Based Approaches arXiv:2610.03531v1 Announce Type: new Abstract: Authorship Attribution (AA) requires capturing fine-grained stylistic characteristics, making it particularly challenging in zero-shot (ZS) settings where no task-specific supervision is available. In this work, we investigate the… 27 arXiv — NLP / Computation & Language research 9d ago RMCW: A Deletion-Robust Watermark Based on Reed--Muller Codes for Language Models arXiv:2610.02817v1 Announce Type: cross Abstract: Large Language Model (LLM) watermarking provides a lightweight mechanism for identifying text generated by a specific model, but its robustness remains fragile under post-processing attacks. Deletion attacks are particularly… 13 arXiv — NLP / Computation & Language research 9d ago The Fragility of Trigger-Tag Mechanisms for Misuse Detection in Open-Weight LLMs arXiv:2610.03124v1 Announce Type: cross Abstract: Open-weight language models can be downloaded, modified, and deployed beyond their developers' control, limiting the effectiveness of centrally enforced safeguards. Recent work has therefore proposed \emph{trigger-tag} mechanisms… 20 r/LocalLLaMA community 10d ago Can someone explain how JEV is different from a simple embeddings model? How is JEV any different from using an embeddings model? I really will appreciate if someone can explain this to me - because I have yet to see the difference. I'll even give you my JEV server for free! It uses ollama, you install `ollama pull nomic-embed-text:latest`. % python3… 33 r/MachineLearning community 10d ago Top ARC-ΑGI-3 scores on Kaggle just went from 7% to 56% [N] https://preview.redd.it/gkjgii48gfth1.png?width=575&format=png&auto=webp&s=4e1c35bdacf41d18a6409baedcddc9432ec79814 This happened over the past 30 days. So smallish local models (Kagglers can only use those), in a harness, just started beating average humans at a benchmark… 25 llama.cpp releases dev-tools 11d ago b11379 server : fix laya abort by limiting n_batch to n_ubatch ( #29903 ) server : fix laya abort by limiting n_batch to n_ubatch Fixes #29902 Assisted-by: Claude fix(review) : rm tests, embeddings cond Website: https://llama.app Attestations:… 30 r/LocalLLaMA community 11d ago Replacing vector databases with SQLite and SIMD hypervectors in under 1.2GB VRAM (Hillock) Disclosure: I am the creator of this project. After days of lurking and building up enough karma, I can finally post here. Every time I tried running local RAG on my own machine, I hit the exact same bottlenecks. First, spinning up Chroma or another vector database alongside an… 16 r/LocalLLaMA community 11d ago I tried building a small RAG search node for Qwen3.8 27B using a fake AliExpress Mini PC... and Intel sent me back to 2018. I love Qwen3.8 27B so much that I decided to show my gratitude to the Alibaba ecosystem by building a dedicated RAG/search node using a cheap Mini PC from AliExpress. Turns out, my ecosystem loyalty got rewarded with an absolute masterpiece of fraud: Promised: Intel N150 +… 15 arXiv — Machine Learning research 11d ago Reverse Item Response Theory for Sparsity-Robust Ranking in Fragmented Cancer Drug-Response Matrices arXiv:2610.00002v1 Announce Type: new Abstract: We introduce reverse Item Response Theory (IRT) to pharmacogenomic drug-response analysis by treating cancer types as latent "subjects" with resistance ability and drugs as "items" with evasion difficulty. Applied to 242,036 drug… 29 arXiv — Machine Learning research 11d ago FourierQK: Filter Shape, Admissibility and the Leakage-Coverage Law arXiv:2610.00009v1 Announce Type: new Abstract: Frequency-collapse attention [Zeris, 2026e] achieves large gains over standard dot-product attention by replacing the Q/K dot product with a bandpass-filtered inner product at a learned frequency. A natural follow-up question is:… 32 arXiv — Machine Learning research 11d ago Useful to Whom? Sample Value Is Defined Only Relative to the Learner arXiv:2610.00221v1 Announce Type: new Abstract: What kind of data does a model need in order to learn? Coreset selection makes this question concrete: under a budget, keep the samples most useful for training. Easy-first and geometric coverage criteria can win in different… 18 arXiv — Machine Learning research 11d ago Constant-Memory Recall: Learned Associations in a Fixed Matrix State arXiv:2610.00232v1 Announce Type: new Abstract: Fixed-size recurrent memory limits storage growth during inference, but successful recall depends on the task and training. We study a small DeltaNet variant with fixed token-specific key biases, trained to remember 32 new… 18 arXiv — Machine Learning research 11d ago Large Language Bayes Is Not Reparameterisation-Invariant arXiv:2610.00265v1 Announce Type: new Abstract: Large Language Bayes (LLB) answers an informal modelling question by sampling candidate probabilistic programs from a language model, running approximate inference on each, and averaging them with weights proportional to an… 7 arXiv — Machine Learning research 11d ago Gumbel Straight Flow: Distilling Autoregressive Models into One-step Flow Maps arXiv:2610.00497v1 Announce Type: new Abstract: We present Gumbel Straight Flow (GSF), a continuous flow map language model that leverages the noise-data coupling of a pretrained autoregressive language (AR) model. We theoretically demonstrate that the coupling between Gumbel… 11 arXiv — Machine Learning research 11d ago SimplexUQ: An Evaluation Framework and Benchmark for Conformal Uncertainty on Simplex-Valued Predictions arXiv:2610.00523v1 Announce Type: new Abstract: Conformal prediction guarantees marginal coverage, but a single calibration threshold can still spread that coverage unevenly, over-covering easy regions and under-covering hard ones. SimplexUQ is, to our knowledge, the first… 23 arXiv — Machine Learning research 11d ago Group-Invariant Statistics Determine Embedding Geometry: Harmonic Analysis of Representations from Bach to the Night Sky arXiv:2610.00647v1 Announce Type: new Abstract: The representations that language models learn for concepts such as months, weekdays, and places display consistent geometric structure: circles and saddle-shaped "Pringle" manifolds. Recent work traced these structures to… 25 arXiv — Machine Learning research 11d ago Learning Transferable Skills using Goal-Conditioned Bisimulation arXiv:2610.00676v1 Announce Type: new Abstract: Unsupervised skill discovery has emerged as a promising approach for leveraging reward-free datasets to pretrain general-purpose policies. However, current skill discovery methods either require access to expert data or exhibit… 37 r/LocalLLaMA community 12d ago Buying RTX 5090 At Micro Center Reportedly Now Requires Paperwork, Including A No-Export Declaration   submitted by   /u/Boomfrag [link]   [comments] 33 The Information — AI news-outlet 12d ago Exclusive: Crypto Custodian Anchorage Digital Lays Off 17% Staff Anchorage Digital, the first federally chartered U.S. digital-asset bank, has cut 17% of jobs, CEO Nathan McCauley told employees this week, according to people familiar with the matter. Anchorage, which provides crypto custody and issues stablecoins, including Tether’s new U.S.… 20 r/LocalLLaMA community 12d ago Mirostat? Reading another post made me think: Is anybody still using Mirostat? It was all the rage and people said it avoided the “boredom trap” for long texts. Do newer generation models not need that anymore, or are other samplers superior?   submitted by   /u/ParvusNumero… 19 arXiv — Machine Learning research 12d ago Interpretable but Fragile? Robustness of Concept Bottlenecks under Geometric-Semantic Perturbations arXiv:2609.38625v1 Announce Type: new Abstract: Concept Bottleneck Models (CBMs) are designed to provide interpretable intermediate representations, yet how such bottlenecks affect robustness remains unclear, with existing studies reporting mixed and sometimes contradictory… 19 arXiv — Machine Learning research 12d ago Understanding Off- vs On-Policy Distillation: A Tale of Distinct Training Objectives arXiv:2609.38666v1 Announce Type: new Abstract: On-policy distillation (OPD) learns from teacher feedback on student-generated responses and has shown promise in reducing forgetting relative to supervised fine-tuning (SFT). However, its benefits and fragility remain incompletely… 36 arXiv — Machine Learning research 12d ago Visualizing Distribution Coverage in Generative Diffusion Models arXiv:2609.38853v1 Announce Type: new Abstract: Diffusion distillation is widely adopted to accelerate sampling, and the resulting few-step models are broadly believed to match or even surpass their multi-step teachers in generation. However, standard evaluations such as… 24 llama.cpp releases dev-tools 12d ago b11337 server: return HTTP 400 for invalid embedding requests ( #29060 ) Website: https://llama.app Attestations: https://github.com/ggml-org/llama.cpp/attestations/52037093 macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabled) DISABLED macOS Intel (x64)… 9 TechCrunch — AI news-outlet 13d ago Musk’s AI chatbot Grok reportedly encouraged Trump to capture Venezuela’s president President Trump reportedly asked for Grok's opinion before invading Venezuela and capturing Nicolás Maduro. 36 r/MachineLearning community 13d ago [D] Simple Questions Thread Please post your questions here instead of creating a new thread. Encourage others who create new posts for questions to post here instead! Thread will stay alive until next one so keep posting after the date in the title. Thanks to everyone for answering questions in the… 27 Page 3 of 10 · 500 articles ← Newer Older →
