News / #rag Tag Rag 500 articles archived under #rag · RSS Sign in to follow arXiv — Machine Learning research 11d ago SIGMA: SHAP-Guided Implicit-Trajectory Generation for Metadata-Free LLM-Based AutoFE arXiv:2608.17948v1 Announce Type: new Abstract: Recent research has leveraged Large Language Models (LLMs) to enhance Automated Feature Engineering (AutoFE) through semantic descriptions and trajectory-based prompting. However, there exist two challenges that limit their… 7 arXiv — NLP / Computation & Language research 11d ago Intent-Driven Dynamic Chunking: Segmenting Documents to Reflect Predicted Information Needs arXiv:2602.14784v1 Announce Type: cross Abstract: Breaking long documents into smaller segments is a fundamental challenge in information retrieval. Whether for search engines, question-answering systems, or retrieval-augmented generation (RAG), effective segmentation determines… 32 arXiv — Machine Learning research 11d ago WONDER: A Radio World Model-based Negotiation Framework for Multi-Agent UAV Coverage Optimization arXiv:2608.16955v1 Announce Type: cross Abstract: Post-disaster damage to terrestrial infrastructure can disrupt wireless coverage,while Uncrewed Aerial Vehicle (UAV) swarms provide a promising solution for rapid restoration.However, due to the limitations in local geometry… 19 arXiv — NLP / Computation & Language research 11d ago There is No Theoretical Curse of Multilinguality For Embedding Space Structure arXiv:2608.17088v1 Announce Type: new Abstract: A central goal of multilingual NLP is to achieve high monolingual performance per language and cross-lingual alignment for large-scale language coverage with a multilingual model. The curse of multilinguality describes the… 22 arXiv — NLP / Computation & Language research 11d ago Towards Safer RAG: Only Agents Capable of System 2 Thinking may Access Untrusted Documents arXiv:2608.17153v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has significantly enhanced the performance of large language models (LLMs), yet these systems remain vulnerable to knowledge-poisoning attacks, in which misinformation in retrieved documents can… 21 arXiv — NLP / Computation & Language research 11d ago CoAL-RAG: A Complexity-Aware Legal Retrieval-Augmented Generation Method arXiv:2608.17536v1 Announce Type: new Abstract: Legal consultation questions exhibit multi-level complexity. A single retrieval strategy often leads to over-reasoning for simple questions and poor interpretability for complex ones, making it difficult to meet the requirements… 6 arXiv — NLP / Computation & Language research 11d ago Preference Is Not Intervention: The Structure and Stability Boundaries of Reader-Specific Evidence Utility arXiv:2608.17781v1 Announce Type: new Abstract: ML systems increasingly condition decisions on downstream model identity, but this is useful only if model-specific differences form reusable structure rather than input-local interactions. We test this in retrieval-augmented… 27 arXiv — NLP / Computation & Language research 11d ago Language Has Two Parameters: Narrative-Induced Semantic Plasticity and Phase-Sensitive Interpretation arXiv:2608.18041v1 Announce Type: new Abstract: Language has two parameters. Count how often words occur together and you estimate amplitude, the strength of association. Word embeddings and attention weights refine that count, which sums every writer in the corpus together.… 36 arXiv — NLP / Computation & Language research 11d ago Reflex-Guard: A Low-Latency Guardrail for LLM Prompt Safety Using Dense Semantic Embeddings arXiv:2608.17556v1 Announce Type: cross Abstract: Large Language Models (LLMs) in real-world applications often face the risks of specially crafted prompts designed to bypass the safety controls. Existing guardrail methods, such as LLM-as-a-judge and cloud-based safety APIs are… 32 arXiv — NLP / Computation & Language research 11d ago On the Fragility of Self-Improving Agents: Variance, Task Order, and Underspecification arXiv:2608.18066v1 Announce Type: cross Abstract: Memory-based self-improving agents--those that learn from an online stream of tasks and improve over time by maintaining a textual memory bank--have shown great promise in recent literature. However, the reliability aspects of… 8 arXiv — NLP / Computation & Language research 11d ago Understanding Undesirable Word Embedding Associations arXiv:1908.06361v2 Announce Type: replace Abstract: Word embeddings are often criticized for capturing undesirable word associations such as gender stereotypes. However, methods for measuring and removing such biases remain poorly understood. We show that for any embedding model… 31 arXiv — NLP / Computation & Language research 11d ago The Authenticity Gap in Human Evaluation arXiv:2205.11930v3 Announce Type: replace Abstract: Human ratings are the gold standard in NLG evaluation. The standard protocol is to collect ratings of generated text, average across annotators, and rank NLG systems by their average scores. However, little consideration has… 11 arXiv — NLP / Computation & Language research 11d ago SimulRAG: Simulator-based RAG for Grounding LLMs in Long-form Scientific QA arXiv:2509.25459v4 Announce Type: replace Abstract: Large Language Models (LLMs) show promise in generating long-form scientific explanations that synthesize evidence and connect multiple factors. However, in long-form scientific question answering, LLMs often hallucinate,… 9 arXiv — NLP / Computation & Language research 11d ago Parametric Knowledge in RAG-SFT for Domain-Specific Document Generation arXiv:2603.23047v2 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) fine-tuning has shown substantial improvements over vanilla RAG, yet most studies target document question answering, leaving open whether these gains transfer to specialized tasks. We study… 19 r/LocalLLaMA community 11d ago Running DeepSeek V4 Flash Q4_K_XL at ~100 tok/s prompt processing on 4× RTX 3060 12GB I managed to run the 143–144 GiB DeepSeek-V4-Flash-0731 UD-Q4_K_XL GGUF on four RTX 3060 12GB cards while keeping a 360k–376k context window. Hardware: CPU: Intel Core i9-10920X, 12C/24T RAM: 128 GB DDR4-3200, quad-channel GPU: 4× NVIDIA RTX 3060 12GB Total VRAM: 48 GB Storage:… 25 Hugging Face Daily Papers research 12d ago AnyTalk: Speech Animation for Arbitrary Characters Leveraging a Video Generation Model Abstract AnyTalk generates 3D speech animations for arbitrary characters without animation data by adapting video diffusion models via character-specific fine-tuning and optimizing blendshape parameters from synthesized talking-head videos, with a distilled real-time variant.… 9 arXiv — Machine Learning research 12d ago Early Cycle Charge Trajectory Generative Prediction and Full Life Cycle Health Management of Iron-Chromium Flow Batteries Based on FlowBD-E1 arXiv:2608.14637v1 Announce Type: new Abstract: Long-duration stationary energy storage requires batteries whose degradation can be detected before substantial capacity loss has accumulated. Iron-chromium redox flow batteries are attractive for this role because they use… 29 arXiv — Machine Learning research 12d ago LUNG-KGMM: Knowledge-Guided Multimodal Learning for Lung Cancer Incidence Prediction arXiv:2608.14657v1 Announce Type: new Abstract: Early identification of lung cancer risk is critical for timely intervention, yet existing prediction models are limited by their reliance on single data modalities and their inability to leverage structured clinical knowledge. We… 12 arXiv — Machine Learning research 12d ago In-Context Learning to Assess Built Environment Impacts on Perceived Neighborhood Walkability Among Mobility-impaired Older Adults arXiv:2608.14663v1 Announce Type: new Abstract: As global populations age, enhancing neighborhood walkability through inclusive urban design is important for mitigating built environment (BE) barriers that discourage physical activity and social participation among older adults.… 32 arXiv — Machine Learning research 12d ago Real-Time State-of-Health Estimation and Online Degradation Prognosis from Partial Battery Discharge Using Physics-Informed Neural Networks arXiv:2608.14764v1 Announce Type: new Abstract: With the increasing integration of renewable energy sources, energy storage systems have become essential, making the accurate estimation of their State of Health (SOH) and degradation behavior critical. In this work, we propose a… 9 arXiv — Machine Learning research 12d ago Structuring Semantic Embeddings for Principle Evaluation: A Prototype-Guided Contrastive Learning Approach arXiv:2608.15224v1 Announce Type: new Abstract: Reliable post-hoc evaluation asks whether already generated text satisfies a target criterion after generation. In this paper we study a focused frozen-embedding setting using principle-evaluation proxy tasks: toxicity detection,… 34 arXiv — Machine Learning research 12d ago SAGA: Structure-Attended Generative Action Embedding Model that encodes Multi-Surface User Action Sequences arXiv:2608.15429v1 Announce Type: new Abstract: Prior embedding models for sequential recommendation typically operate within a homogeneous action space, limiting their ability to capture cross-surface behavioral signals spanning distinct behavioral domains. We present SAGA, a… 25 arXiv — NLP / Computation & Language research 12d ago Where Does Retrieval Fail? Evaluating RAG Architectures for Agricultural Advisory arXiv:2608.14886v1 Announce Type: new Abstract: Retrieval quality in RAG systems is commonly reported as a single aggregate score, which can hide large differences across query types and language conditions. We study this problem in Bengali agricultural advisory, where farmer… 23 arXiv — NLP / Computation & Language research 12d ago Interpretable Cross-Lingual Alignment in Small Language Models: Probing Cultural and Pragmatic Reasoning in Japanese-English Bilingual LLMs arXiv:2608.14896v1 Announce Type: new Abstract: Large language models work well on English and behave in poorly understood ways on languages typologically far from it. Japanese is a clean example, where evaluation still leans on translation quality and JGLUE-style benchmarks,… 21 arXiv — NLP / Computation & Language research 12d ago Logical Embeddings for Argument Analysis arXiv:2608.15325v1 Announce Type: new Abstract: We propose a new framework for machine-learning-oriented argument analysis tasks. Our proposal involves replacing traditional contextualized word embeddings used in most NLP tasks with logical embeddings, an alternative encoding… 12 arXiv — NLP / Computation & Language research 12d ago BengaliMCQ: Automatic Generation and Answer Prediction of Academic Multiple-Choice Questions in a Low-Resource Language arXiv:2608.15547v1 Announce Type: new Abstract: Traditional retrieval-augmented generation (RAG) frameworks process documents without attending to their hierarchical structure, leading to poor performance, especially in low-resource languages such as Bengali. To address this, we… 28 arXiv — NLP / Computation & Language research 12d ago LENS: In-Context Search via Latent Evidence Exploration over Dynamic Raw Documents arXiv:2608.16185v1 Announce Type: new Abstract: LLM agents increasingly answer questions over dynamic raw-document collections, where files may change before preprocessing, and relevant evidence (spans, sections, pages, or tables) is query-dependent. Existing retrieval-augmented… 38 arXiv — NLP / Computation & Language research 12d ago STAIR: Semantic-Temporal Automaton for Interpretable Reasoning in Temporal Question Answering arXiv:2608.16224v1 Announce Type: new Abstract: By leveraging large-scale pretraining, LLMs can interpret diverse temporal expressions and question formulations without task-specific training. However, existing prompt-based neuro-symbolic systems continue to rely on LLMs for… 11 arXiv — NLP / Computation & Language research 12d ago Domain-Agnostic Neural Topic Modeling with Contextual Token-Level Semantic Graph Representation arXiv:2608.16269v1 Announce Type: new Abstract: Recent advances in neural topic models with pre-trained language models (PLMs) have achieved strong performance by leveraging general-domain pre-training, yet their topic interpretability often degrades on specialized corpora. This… 4 arXiv — NLP / Computation & Language research 12d ago Clause Encounters of the Third Kind: Can LLMs Replace Language Teachers? arXiv:2608.16286v1 Announce Type: new Abstract: While various organizations now actively encourage LLM use in classrooms, we still lack rigorous, systematic evaluations of how well these models actually perform the fundamental tasks of language pedagogy. This paper examines… 13 arXiv — NLP / Computation & Language research 12d ago HalluTracer: Hallucination Detection via Depth-Averaging Truth Signals arXiv:2608.16353v1 Announce Type: new Abstract: Even well-aligned large language models confidently generate factually incorrect text, making hallucination a persistent reliability risk in high-stakes deployments. These models nonetheless carry linearly separable truthfulness… 18 arXiv — NLP / Computation & Language research 12d ago Counting Documents Is Not Counting Text: Unit Bias in Web-PDF Corpus Statistics arXiv:2608.16390v1 Announce Type: new Abstract: PDF corpora advertise their size in tokens but compute every rate they publish (coverage, OCR routing, re-fetch recovery, language mix) per document, and none decomposes its token total. The two units diverge sharply. On… 16 arXiv — NLP / Computation & Language research 12d ago D2-ScaleAgent: Dual-Dimensional Scaling for Long Document Understanding arXiv:2608.16417v1 Announce Type: new Abstract: Multi-modal retrieval-augmented generation (RAG) is a key technique for visually rich long document understanding. Existing multi-modal RAG methods are progressively advancing toward multi-agent systems: they first retrieve… 32 arXiv — NLP / Computation & Language research 12d ago When Context Misleads: Intent-Guided Decoding for Robust Retrieval-Augmented Generation arXiv:2608.16515v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves large language models by grounding generation in external evidence, but it also introduces a source trust problem: retrieved context may be useful, irrelevant, or even misleading.… 37 Hugging Face Daily Papers research 12d ago When Context Bites: Detecting RAG Poisoning via Document-Level Attention Collapse Abstract D-SCAN detects retrieval poisoning by monitoring attention collapse dynamics in language model generations. Generated by thinkingmachines/Inkling-Small Retrieval-augmented generation (RAG) is indispensable for enhancing large language models. However, RAGs are… 23 Hugging Face Daily Papers research 12d ago Ventor-QTest: Threat-Model-Driven Verification of Vendor-Hosted LLM APIs Abstract Ventor-QTest audits hosted open-weight model APIs via repeated and long-sequence black-box probes, measuring average and extreme fidelity loss to detect degradation in long-horizon agentic performance. Generated by thinkingmachines/Inkling-Small As large language models… 35 Hugging Face official-blog 12d ago Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers Back to Articles a]:hidden"> Multi-Vector (Late Interaction) Embedding Models with Sentence Transformers Published August 18, 2026 Update on GitHub Upvote 4 Tom Aarsen tomaarsen Antoine Chaffin NohTow lightonai Raphael Sourty raphaelsty lightonai Sentence Transformers is a… 17 r/MachineLearning community 12d ago We’ve got a workshop on production retrieval-augmented generation with open models, benchmarked end to end, thought it’d be relevant here [D] There’s a hands-on workshop on August 29 that builds and benchmarks this properly, end to end, using entirely open models, no API calls involved. Led by Ben Auffarth, AI Consultant and Founder of Chelsea AI Ventures. What it covers: • Hybrid retrieval (vector + keyword, not… 6 Hacker News — AI on Front Page community 12d ago Universal Health Coverage Could Save $1T and 114k Lives a Year, Yale Study Article URL: https://ysph.yale.edu/news-article/universal-health-coverage-could-save-one-trillion-dollars-and-114000-lives-every-year/ Comments URL: https://news.ycombinator.com/item?id=49332981 Points: 207 # Comments: 262 29 Hugging Face Daily Papers research 12d ago Who Speaks Matters: Authority-Aware Multi-View RAG over Italian Parliamentary Proceedings Abstract ParliamentRAG is a retrieval-augmented generation system for Italian parliamentary records that uses topic-dependent speaker authority to retrieve expert perspectives and generate faithful, multi-perspective summaries. Generated by thinkingmachines/Inkling-Small… 24 r/LocalLLaMA community 12d ago tencent/EVIE-Preview-4.5B · Hugging Face Overview EVIE-Preview-4.5B is a state-of-the-art multilingual Visual Document Retrieval (VDR) model built upon Qwen3.5-4B . It employs ColBERT-style late interaction with native 128-dimensional multi-vector token embeddings (4.54B parameters, BF16). By combining native… 37 MIT Technology Review — AI news-outlet 13d ago What happens when a kid’s robot best friend dies? When Xander first met Moxie, she taught him that when he was anxious, he could calm down by exhaling through his lips so that he buzzed like a bee. They practiced breathing like dragons to manage feeling mad and sniffing like bunnies to boost his energy. But in the six years… 17 Hugging Face Daily Papers research 13d ago Intern-S2-Mobius: Foundation Model with Decoupled Knowledge and Reasoning Abstract Mobius-v0 separates global memory storage from iterative reasoning modules to improve knowledge compression and inference efficiency, yielding comparable performance with less training data and faster inference. Generated by thinkingmachines/Inkling-Small We introduce… 24 Hugging Face Daily Papers research 13d ago Generation as Auxiliary Supervision: Enhancing Visual Understanding at Zero Inference Overhead via Decoupled Embedding Prediction Abstract GAS improves multimodal understanding by using generation as auxiliary supervision via next embedding prediction and a decoupled mixture-of-transformers architecture, with no inference overhead. Generated by thinkingmachines/Inkling-Small While Multimodal Large Language… 19 arXiv — NLP / Computation & Language research 13d ago Geometric Filtering of LLM-Generated Samples for Few-Shot Text Classification arXiv:2608.13866v1 Announce Type: cross Abstract: Large language models (LLMs) can generate synthetic training data for text classification, but the quality of generated samples is heterogeneous: some fall in correct class regions of the embedding space while others land in… 21 arXiv — Machine Learning research 13d ago Model-agnostic Retrieval-Augmented Extended Forecasting for time series arXiv:2608.14054v1 Announce Type: new Abstract: Time series forecasting with pretrained foundation models has demonstrated strong zero-shot capabilities. However, achieving optimal performance on time series with short or negligible historical data in domain-specific… 15 arXiv — Machine Learning research 13d ago Training Fair Tabular Foundation Models arXiv:2608.14211v1 Announce Type: new Abstract: Tabular Foundation Models (TFMs) have emerged as leading methods for tabular predictive tasks, leveraging in-context learning to predict on new data without task-specific training. Despite the increased use of TFMs in high-stakes… 27 arXiv — Machine Learning research 13d ago Boosting Data Augmentation with Stochastic Weight Averaging arXiv:2608.14373v1 Announce Type: new Abstract: The symmetries of a learning task have become an important factor in designing modern deep learning solutions. Data augmentation is a straightforward and effective way of incorporating symmetries into a generic neural network.… 6 arXiv — Machine Learning research 13d ago Designing Reinforcement Learning for Diffusion Models: A Unified Path-Space View arXiv:2608.14430v1 Announce Type: new Abstract: Reinforcement learning (RL) post-training provides a direct way to align diffusion models with human preferences and task-specific rewards. However, current RL algorithms for diffusion models remain fragmented: reverse-trajectory… 38 arXiv — NLP / Computation & Language research 13d ago Think in Latent, Explain in Language: Self-Explainable Latent Reasoning arXiv:2608.13570v1 Announce Type: new Abstract: Latent reasoning has emerged as a powerful alternative to text-based Chain-of-Thought (CoT), offering significant gains in computational efficiency by compressing verbose reasoning into compact embeddings. However, compressing… 28 Page 4 of 10 · 500 articles ← Newer Older →
