News / #rag Tag Rag 500 articles archived under #rag · RSS Sign in to follow arXiv — Machine Learning research 26d ago On Out-of-sample Embedding in UMAP arXiv:2606.04451v1 Announce Type: new Abstract: Neighbor embedding algorithms reveal correlations in high-dimensional data by constructing an equivalent graph representation in a lower-dimensional space. An increasingly popular algorithm is Uniform Manifold Learning and… 34 arXiv — Machine Learning research 26d ago Learning symplectic model reduction based on a approximation theorem of symplectic embeddings arXiv:2606.04623v1 Announce Type: new Abstract: High-dimensional Hamiltonian systems play a central role in many scientific and engineering disciplines, with dynamics evolving on symplectic manifolds. Although deep learning provides powerful tools for constructing… 9 arXiv — Machine Learning research 26d ago Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation arXiv:2606.04665v1 Announce Type: new Abstract: Deep unsupervised domain adaptation (Deep UDA) methods successfully leverage rich labeled data in a source domain to boost the performance on related but unlabeled data in a target domain. However, algorithm comparison is… 23 arXiv — Machine Learning research 26d ago Curvature-aware dynamic precision approach for physics-informed neural networks arXiv:2606.04736v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) have become a promising framework for simulating partial differential equations (PDEs) by embedding physical laws directly into neural network training. However, recent studies show that… 24 arXiv — NLP / Computation & Language research 26d ago When Retrieval Doesn't Help: A Large-Scale Study of Biomedical RAG arXiv:2606.04127v1 Announce Type: new Abstract: Medical question answering is a high-stakes setting where factual errors can have serious consequences. Retrieval-augmented generation (RAG) is widely viewed as a promising solution, and prior work has reported substantial gains… 35 arXiv — NLP / Computation & Language research 26d ago MM-BizRAG: Rethinking Multimodal Retrieval-Augmented Generation for General Purpose Enterprise Q&A arXiv:2606.04231v1 Announce Type: new Abstract: Recent advances in multimodal retrieval-augmented generation (MM-RAG) have shifted toward minimal parsing, relying on page-level images for producing retriever embeddings and for answer generation. While efficient, this trend often… 24 arXiv — NLP / Computation & Language research 26d ago LazyAttention: Efficient Retrieval-Augmented Generation with Deferred Positional Encoding arXiv:2606.04302v1 Announce Type: new Abstract: Key-value (KV) caching accelerates inference of large language models (LLMs) by reusing past computations for generated tokens. Its importance becomes even greater in long-context applications such as retrieval-augmented generation… 10 arXiv — NLP / Computation & Language research 26d ago DLLG: Dynamic Logit-Level Gating of LLM Experts arXiv:2606.04378v1 Announce Type: new Abstract: Leveraging multiple specialized LLMs can combine complementary strengths, but existing approaches trade adaptability for stability: routing commits prematurely, heuristic ensembling depends on fragile proxies, and parameter merging… 38 arXiv — NLP / Computation & Language research 26d ago GENEB: Why Genomic Models Are Hard to Compare arXiv:2606.04525v1 Announce Type: new Abstract: Progress in genomic foundation models is difficult to assess due to fragmented benchmarks, incompatible evaluation protocols, and task-specific reporting. As a result, claims of superiority or generality across models are often not… 26 arXiv — NLP / Computation & Language research 26d ago Fine-grained Fragment Retrieval in Multi-modal Long-form Dialogues arXiv:2606.04591v1 Announce Type: new Abstract: With the widespread adoption of multi-modal communication platforms, long-form dialogues interleaving text and images have become increasingly common. Users often need to retrieve coherent dialogue fragments related to specific… 27 arXiv — NLP / Computation & Language research 26d ago QO-Bench: Diagnosing Query-Operator-Preserving Retrieval over Typed Event Tuples arXiv:2606.04646v1 Announce Type: new Abstract: Many real-world questions over business, legal, and scientific corpora are natural-language versions of database-style queries over records latent in text. Existing retrieval-augmented generation (RAG) systems are optimized… 6 arXiv — NLP / Computation & Language research 26d ago Exploring the Topology and Memory of Consensus: How LLM Agents Agree, Fragment, or Settle When Forming Conventions arXiv:2606.04197v1 Announce Type: cross Abstract: How much should an LLM agent remember, and how should multi-agent systems be connected when trying to reach consensus? We show these two design choices interact in a way that flips the sign of memory's effect on coordination.… 12 arXiv — NLP / Computation & Language research 26d ago Overview of the EReL@MIR 2025 Multimodal Document Retrieval Challenge (Track 1) arXiv:2606.04240v1 Announce Type: cross Abstract: Retrieval over visually-rich documents, pages that interleave text with figures, tables, and charts, is essential for multimodal retrieval-augmented generation, yet most retrievers still discard the visual channel. The… 7 arXiv — NLP / Computation & Language research 26d ago Cascading Hallucination in Agentic RAG: The CHARM Framework for Detection and Mitigation arXiv:2606.04435v1 Announce Type: cross Abstract: Multi-step agentic retrieval-augmented generation (RAG) pipelines have demonstrated significant capability for complex reasoning tasks, yet remain vulnerable to a class of failure that existing hallucination detection mechanisms… 25 Hugging Face Daily Papers research 26d ago Streaming Communication in Multi-Agent Reasoning Abstract StreamMA enables efficient multi-agent reasoning by streaming intermediate results and leveraging reliable early steps to improve both latency and effectiveness across various reasoning tasks. Generated by Qwen/Qwen2.5-Coder-32B-Instruct Multi-agent reasoning systems… 12 r/LocalLLaMA community 26d ago How can the numbers be this massive within a month ?? Why does it feel like these downloads are just inflated by the brain dead enterprises whose employees even after exhausting their $ 1500 montly credits are not able to cache it in a shared storage by prompting their AI waifu "Do not download it ever again every time my container… 17 r/LocalLLaMA community 26d ago Best way to index full Italian Wikipedia for 100% offline RAG in LM Studio? Hi everyone, I want to set up a 100% offline RAG system using LM Studio and the entire Italian Wikipedia (text-only, no images). My goal is to index the database once so my local LLMs can query it for up-to-date factual knowledge without internet access. Here are my PC specs:… 14 Hugging Face Daily Papers research 26d ago Bootstrap Your Generator: Unpaired Visual Editing with Flow Matching Abstract Bootstrap Your Generator framework enables unpaired training of flow matching editing models by leveraging base model knowledge and gradient routing for improved generalization in data-scarce scenarios. Generated by Qwen/Qwen2.5-Coder-32B-Instruct Modern generative… 18 Hugging Face Daily Papers research 26d ago OCC-RAG: Optimal Cognitive Core for Faithful Question Answering Abstract Compact task-specialized language models demonstrate superior performance in multi-hop reasoning and faithfulness compared to larger general-purpose models through a novel training pipeline and structured reasoning traces. Generated by Qwen/Qwen2.5-Coder-32B-Instruct… 32 r/LocalLLaMA community 27d ago Mellum & Granite Embedding models are ready on llama.cpp https://github.com/ggml-org/llama.cpp/pull/23966 https://github.com/ggml-org/llama.cpp/pull/22716 Use llama.cpp version.   submitted by   /u/pmttyji [link]   [comments] 22 arXiv — Machine Learning research 27d ago Auditable Climate Risk Intelligence from Fragmented ESG Data: Deterministic Orchestration and Imbalance-Aware Learning for Scope 1-3 Validation arXiv:2606.02604v1 Announce Type: new Abstract: ESG and climate risk data remain fragmented across heterogeneous Scope 1, Scope 2, and Scope 3 reporting environments, while conventional validation pipelines lack provenance aware auditability, hidden drift detection, and… 9 arXiv — Machine Learning research 27d ago Calibration Data Trade-offs Across Capability Dimensions: Why Multi-Source Mixing Matters for High-Sparsity LLM Pruning arXiv:2606.03328v1 Announce Type: new Abstract: Post-training pruning compresses large language models to high sparsity using a small unlabelled calibration set, and recent work has concluded that the choice of calibration source has only modest impact on averaged post-pruning… 27 arXiv — Machine Learning research 27d ago Link Prediction or Perdition: the Seeds of Instability in Knowledge Graph Embeddings arXiv:2606.03365v1 Announce Type: new Abstract: Embedding models (KGEMs) constitute the main link prediction approach to complete knowledge graphs. Standard evaluation protocols emphasize rank-based metrics such as MRR or Hits@$K$, but usually overlook the influence of random… 26 arXiv — NLP / Computation & Language research 27d ago A Locally Deployed RAG-Based Academic Advising System for Course Selection arXiv:2606.02983v1 Announce Type: new Abstract: The correct sequence of courses in the curriculum based on prerequisites between courses is of great importance for students to develop their knowledge and skills holistically. However, students crafting this sequence in isolation… 25 arXiv — NLP / Computation & Language research 27d ago SEA-Embedding: Open and Reproducible Text Embeddings for Southeast Asia arXiv:2606.03027v1 Announce Type: new Abstract: Text embeddings are fundamental to many downstream applications, making robustness important for real-world NLP. However, most recent state-of-the-art embedding models are not reproducible because they rely on closed or undisclosed… 17 arXiv — NLP / Computation & Language research 27d ago When Does Complexity Conditioning Help a Frozen Sentence Embedding? A Controlled Study of Per-Sentence and Pair-Level Difficulty Adaptation arXiv:2606.03244v1 Announce Type: new Abstract: A common intuition is that sentence embeddings should adapt to the difficulty of the input. We test this intuition in a controlled, multi-seed setting: a lightweight post-encoder adapter attaches to a frozen Qwen3-Embedding-0.6B… 11 arXiv — NLP / Computation & Language research 27d ago Beyond the Literal: Decomposing Pragmatic Intent in Multimodal Meme Understanding arXiv:2606.03604v1 Announce Type: new Abstract: When asked what a meme or sarcastic post means, Large Vision Language Models (LVLMs) tend to describe what the image shows rather than what the author is trying to communicate. Standard instruction tuning entangles a post's literal… 37 arXiv — NLP / Computation & Language research 27d ago Don't Forget Your Embeddings: Robust Knowledge Erasure via Precise Editing of Embeddings arXiv:2606.03695v1 Announce Type: new Abstract: As language models are increasingly deployed in real-world applications, the ability to erase specific knowledge from them becomes critical for safety and compliance. Prominent methods seek persistent removal by updating the… 19 arXiv — NLP / Computation & Language research 27d ago Re-Ranking Through an Attribution Lens for Citation Quality in Legal QA arXiv:2606.03728v1 Announce Type: new Abstract: Retrieval-augmented generation systems for legal question answering typically retrieve passages based on semantic similarity and provide them to a language model, which then generates cited answers. Prior work assumes that highly… 4 arXiv — NLP / Computation & Language research 27d ago Consistency Training Can Entrench Misalignment arXiv:2606.03810v1 Announce Type: new Abstract: Consistency training encourages a model to produce similar outputs across related inputs or sampling procedures. Such methods are simple, scalable, and largely label-free, but their effects on model alignment remain poorly… 31 arXiv — NLP / Computation & Language research 27d ago VESTA: Visual Exploration with Statistical Tool Agents arXiv:2606.00384v1 Announce Type: cross Abstract: Fitting quantitative models to data is a central step in scientific workflows, yet it remains one of the least automated. Recent agent-based systems leverage language and vision-language models (VLMs) to iteratively propose and… 10 Hugging Face Daily Papers research 27d ago Decentralized Instruction Tuning: Conflict-Aware Splitting and Weight Merging Abstract Instruction tuning of large language models can be improved through decentralized training that partitions mixed datasets based on gradient conflicts and merges results via weighted averaging, achieving performance comparable to centralized methods with reduced… 16 TechCrunch — AI news-outlet 27d ago Uber caps employee AI spending after blowing through budget in four months Uber's cutback has occurred after the company had reportedly encouraged staff to use AI as much as possible. 26 llama.cpp releases dev-tools 27d ago b9481 model : support granite multilingual embeddings R2 (ibm-granite/granite-embedding-{97,311}m-multilingual-r2) ( #22716 ) Add support for the ibm-granite/granite-embedding-{97m,311m}-multilingual-r2 embedding models: Added a version of the gpt4o tokenizer that has a fixed regex… 22 Hugging Face Daily Papers research 27d ago Same Question, Different Source, Different Answer: Auditing Source-Dependence in Medical Multi-Source RAG Abstract Retrieval-augmented generation systems exhibit source-dependent responses to identical queries, necessitating a shift from traditional correctness evaluation to analyzing inter-source relationships for multi-source NLP systems. Generated by… 17 Hugging Face Daily Papers research 27d ago Linear Ensembles Wash Away Watermarks: On the Fragility of Distributional Perturbations in LLMs Abstract Watermarking AI-generated text for detection fails when multiple models are used, as averaging outputs cancels perturbations and suppresses detection while improving quality and speed. Generated by Qwen/Qwen2.5-Coder-32B-Instruct Watermarking embeds statistical… 4 Hugging Face Daily Papers research 27d ago ACL-Verbatim: hallucination-free question answering for research Abstract Researchers develop a VerbatimRAG-based extractive question answering system using a novel ground truth dataset and ModernBERT model to improve accurate information retrieval from research papers. Generated by Qwen/Qwen2.5-Coder-32B-Instruct Academic researchers need… 38 MIT Technology Review — AI news-outlet 27d ago Rehumanizing global health care with agentic AI The global health care sector is under increasing strain.  Decades of chronic underinvestment and constraints in recruitment have coincided with a surge in demand for services for aging populations. Gaps in provision are already taking a toll, with fragmented access to care… 19 Hugging Face Daily Papers research 28d ago Geometric Latent Reasoning Induces Shorter Generations in LLMs Abstract Geometric Latent Reasoning formulates latent reasoning as a geometric path-approximation problem in pretrained token-embedding space, enabling continuous intermediate reasoning states that reduce generation length while maintaining accuracy. Generated by… 6 MIT Technology Review — AI news-outlet 28d ago How small businesses can leverage AI This article is from Making AI Work, MIT Technology Review’s limited-run newsletter examining how to apply LLMs across industries. To receive it in your inbox,sign up here. From accounting to design to market research and product development, there’s a staggering breadth of… 4 Hugging Face Daily Papers research 28d ago Adapting Multilingual Embedding Models to Turkish via Cross-Lingual Tokenizer Surgery and Offline Distillation Abstract A Turkish-focused sentence embedding model is developed through efficient adaptation techniques, achieving superior performance with reduced computational costs compared to larger teacher models. AI-generated summary Sentence embeddings are a foundational component for… 37 Hugging Face Daily Papers research 28d ago A Matter of TASTE: Improving Coverage and Difficulty of Agent Benchmarks Abstract Automated benchmark generation method creates challenging tasks with broader tool-use coverage by evolving tool sequences through adaptive contrastive n-gram modeling and iterative difficulty refinement. AI-generated summary As agent capabilities advance, existing… 31 Hugging Face Daily Papers research 28d ago LongLive-RAG: A General Retrieval-Augmented Framework for Long Video Generation Abstract LongLive-RAG addresses long-video generation challenges by using retrieval-augmented generation to overcome error accumulation from sliding-window attention, enabling better temporal coherence and quality. AI-generated summary Autoregressive (AR) video diffusion enables… 22 arXiv — Machine Learning research 28d ago Canonicalized Stable-List Replay for Private Federated Continual Learning over Language-Model Embeddings arXiv:2606.00426v1 Announce Type: new Abstract: Federated continual learning (FCL) lets distributed clients adapt language-model heads to evolving NLP tasks without sharing raw text. Under user-level differential privacy (DP), replay-based continual learning faces a structural… 17 arXiv — Machine Learning research 28d ago Grounded Decoding: Retrieval-Anchored Probability Fusion for Faithful RAG arXiv:2606.00432v1 Announce Type: new Abstract: As retrieval-augmented generation (RAG) systems scale, it becomes increasingly challenging to ensure faithful grounding in external evidence. Large language models may still prioritize parametric knowledge over retrieved… 13 arXiv — NLP / Computation & Language research 28d ago Toward Robust In-Context Learning: Leveraging Out-of-distribution Proxies for Target Inaccessible Demonstration Retrieval arXiv:2606.00014v1 Announce Type: new Abstract: Although studies have demonstrated that Large Language Models (LLMs) can perform well on Out-of-Distribution (OOD) tasks, their advantage tends to diminish as the distribution shift becomes more severe. Consequently, researchers… 33 arXiv — NLP / Computation & Language research 28d ago SENSE: Semantic Embedding Navigation with Soft-gated Evaluation for Retrieval-based Speculative Decoding arXiv:2606.00021v1 Announce Type: new Abstract: Speculative Decoding (SD) accelerates Large Language Model (LLM) inference by employing a lightweight draft model to propose candidate tokens, which are verified in parallel by the target model, without compromising generation… 17 arXiv — NLP / Computation & Language research 28d ago Cognitive-Linguistic Indicators of Depression in Online Communities: Analysed by DistilBERT and Holographic Reduced Representation arXiv:2606.00026v1 Announce Type: new Abstract: This paper investigates whether combining cognitively grounded linguistic features with transformer-based embeddings improves automated detection of depression in online text. Using Beck's Cognitive Theory of Depression, the study… 27 arXiv — NLP / Computation & Language research 28d ago TCAR-Gen: Temporal Graph Retrieval with Evidence Fusion for Knowledge-Grounded Generation arXiv:2606.00029v1 Announce Type: new Abstract: Retrieval-augmented generation systems struggle with temporal reasoning and evidence fusion when answering complex questions over historical criminal case narratives. Existing approaches either retrieve independently of query… 18 arXiv — NLP / Computation & Language research 28d ago Graph-Augmented Retrieval for Cross-Entity Financial Sentiment Analysis: A Comparative Study arXiv:2606.00062v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become foundational for grounding large language models in domain-specific corpora, yet conventional vector-based RAG systems are fundamentally limited in their ability to capture the… 23 Page 8 of 10 · 500 articles ← Newer Older →
