News / #rag Tag Rag 500 articles archived under #rag · RSS Sign in to follow arXiv — Machine Learning research 27d ago Mitigating Class-Tail Undercoverage in Medical Vision-Language Models under Clinical Shift arXiv:2607.28696v1 Announce Type: new Abstract: Medical vision-language models (VLMs) can retain high observed marginal coverage after clinical shift while substantially under-covering an individual disease class. The affected class varies with acquisition protocol and backbone… 9 arXiv — Machine Learning research 27d ago Flow Matching with Missing Data arXiv:2607.28698v1 Announce Type: new Abstract: Flow matching assumes fully observed training data, which many real-world applications rarely provide. We propose Missing-Data Flow Matching, which treats the missing coordinates of training samples as latent variables and averages… 24 arXiv — Machine Learning research 27d ago PiDDM: Physics-Informed Differentiable Degradation Modeling for Lithium-Ion Battery State-of-Health Prediction arXiv:2607.29095v1 Announce Type: new Abstract: Accurate prediction of lithium-ion battery state of health (SOH) is essential for reliable energy storage operation. However, purely data-driven models may generalize poorly across cycling protocols and produce physically… 27 arXiv — Machine Learning research 27d ago Exploring Block Anomaly Detection In HDFS Log Data Analysis arXiv:2607.29383v1 Announce Type: new Abstract: In recent years, with the development of big data technology, increasingly more companies use HDFS for data processing and storage. As a result, the maintenance of distributed file systems has become an extremely important part of… 6 arXiv — NLP / Computation & Language research 27d ago Tokenizer-Agnostic Engram Module arXiv:2607.29065v1 Announce Type: new Abstract: Deepseek's Engram, a conditional memory module, was introduced to trade-off storage versus reasoning in large language models. However, the module relies on token-level $N$-gram hashing for Engram embedding lookup, introducing a… 31 arXiv — NLP / Computation & Language research 27d ago Adjudicated Captioning: Multi-Agent Alignment Scoring and Consensus-Distilled Beam Arbitration for Strict Zero-Shot Image Captioning arXiv:2607.28986v1 Announce Type: cross Abstract: Zero-shot image captioning (ZIC) describes images without paired image-caption supervision during captioner training, relying on text-only corpora and frozen pretrained image-text scorers. Existing retrieval-augmented methods… 26 arXiv — NLP / Computation & Language research 27d ago GoldenRetriever: Non-Interactive Homomorphic Encrypted Retrieval for Privacy-Preserving RAG arXiv:2607.29019v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enhances large language models by incorporating external knowledge, but existing pipelines typically operate on plaintext data, raising significant privacy concerns. Prior work on… 37 arXiv — NLP / Computation & Language research 27d ago Bridging the Question-Answer Gap in Retrieval-Augmented Generation: Hypothetical Prompt Embeddings arXiv:2607.29402v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) systems synergize retrieval mechanisms with generative language models to enhance the accuracy and relevance of responses. However, bridging the style gap between user queries and relevant… 23 arXiv — NLP / Computation & Language research 27d ago When Iterative RAG Beats Ideal Evidence: A Diagnostic Study in Scientific Multi-hop Question Answering arXiv:2601.19827v5 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) extends large language models (LLMs) beyond parametric knowledge, yet it is unclear when iterative retrieval-reasoning loops meaningfully outperform static RAG, particularly in scientific… 36 r/MachineLearning community 29d 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… 20 r/MachineLearning community 29d ago Meh-Compression [D] Compression by switched linear matrix compression. Backpropagation teaches - when this matrix is selected - this is the best (on average) linear mapping to use: https://archive.org/details/switched-linear-matrix-compression   submitted by   /u/oatmealcraving [link]  … 9 Hugging Face Daily Papers research 1mo ago ReToken: One Token to Improve Vision-Language Models for Visual Retrieval Abstract Long visual context poses a challenge for vision-language models: performance degrades as the number of distractors grows, and processing all tokens at once is computationally infeasible under GPU memory constraints. We present ReToken, a single learnable embedding… 22 Hugging Face Daily Papers research 1mo ago See2Think: Do Multimodal Models Really Use Intermediate Visual States? Abstract Multimodal large language models increasingly use sketches, annotations, tools, and intermediate images during reasoning, but it remains unclear whether they truly rely on these visual states. Existing benchmarks are limited both by task collections with narrow coverage… 9 arXiv — Machine Learning research 1mo ago A Lightweight Foundation Model for Collider Physics with Multi-Domain Adaptation arXiv:2607.27501v1 Announce Type: new Abstract: We present a lightweight approach to foundation modeling (\textbf{NEXUS}) that leverages pre-trained learning from collider physics data towards out-of-domain tasks in other scientific datasets, using a fully connected autoencoder… 33 arXiv — Machine Learning research 1mo ago When Does Explicit View Routing Work? A Controlled Study of Multi-View Graph-Text Alignment arXiv:2607.27530v1 Announce Type: new Abstract: Graph-text retrieval typically maps a graph and its description to a single embedding, even when a query concerns only one semantic aspect, such as a class label or molecular property. Multiple heads can separate these aspects, but… 23 arXiv — Machine Learning research 1mo ago First-order Constrained Trilevel Optimization Over Distributed Networks for Robust Coreset Selection arXiv:2607.27632v1 Announce Type: new Abstract: With the rapid advancement of the Internet of Things (IoT), massive amounts of data are generated across distributed edge networks. Training models on full data incurs significant computational overhead and storage bottlenecks,… 4 arXiv — Machine Learning research 1mo ago Revisiting Predictive Process Monitoring in the Age of Foundation Models: A Comparative Study of Sequence, Tabular, and LLM Approaches arXiv:2607.27797v1 Announce Type: new Abstract: Predictive process monitoring (PPM) leverages event logs to forecast the future of running process instances, for instance, predicting the next activity, the remaining time until case completion, or the time to the next event.… 5 arXiv — Machine Learning research 1mo ago S-CEReBrO: Breaking the Memory Barrier in Continuous EEG Monitoring arXiv:2607.27913v1 Announce Type: new Abstract: Foundation models offer a promising paradigm for Electroencephalography (EEG) analysis, leveraging generalizable representations from vast unlabeled datasets. Yet, Transformer-based architectures face a critical bottleneck: global… 9 arXiv — Machine Learning research 1mo ago Chem World: A Large-Scale Benchmark and Physics-Informed Framework for Trustworthy Chemical Property Prediction arXiv:2607.28079v1 Announce Type: new Abstract: Chemical property prediction plays a critical role in accelerating scientific discovery in chemistry, materials science, and drug development. However, existing benchmarks often suffer from limited task diversity, fragmented… 24 arXiv — NLP / Computation & Language research 1mo ago LayerRAG-Bench: A Cross-Layer Reliability Benchmark for Agentic Retrieval-Augmented Generation arXiv:2607.27353v1 Announce Type: new Abstract: Agentic retrieval-augmented generation systems can produce answers that appear grounded while failing at the evidence, tool-contract, authorization, or session-state layer. We introduce LayerRAG-Bench, a controlled cross-layer… 36 arXiv — NLP / Computation & Language research 1mo ago Models for minimalist RAG: B1ade 335M Embedding and 1B Parameter Small Language Models arXiv:2607.27506v1 Announce Type: new Abstract: Language and embedding models used in RAG systems are conventionally assumed to require large-scale pretraining and explicit grounding supervision. We present B1ade, an efficient RAG architecture comprising two purpose-built… 36 arXiv — NLP / Computation & Language research 1mo ago Correlation between prosody and pragmatics: A case study of the discourse marker h\=al\=a `now' in Persian arXiv:2607.28359v1 Announce Type: new Abstract: The Persian discourse marker h\=al\=a ('now') exhibits remarkable multifunctionality, extending far beyond its temporal adverbial role to encompass a variety of pragmatic functions. This study presents a pragmatic and acoustic… 35 arXiv — NLP / Computation & Language research 1mo ago MemTxn: A Transaction Boundary for Source-Supported Updates and Complete-State Recovery in Agent Memory arXiv:2607.27834v1 Announce Type: cross Abstract: Persistent memory lets long-running large language model agents reuse information across sessions and tasks. Yet errors in writable memory can persist and corrupt future behavior. Existing systems improve storage and retrieval,… 18 arXiv — NLP / Computation & Language research 1mo ago CDAE: Enhancing Perturbation Robustness in Pretrained Language Models with Contrastive Denoising arXiv:2607.28236v1 Announce Type: cross Abstract: Pre-trained language models have significantly improved sentence representation learning, yet their embedding remain sensitive to semantic preserving textual perturbations such as synonym substitution, masking and word dropout.… 19 arXiv — NLP / Computation & Language research 1mo ago GLM-RAG: Graph Language Models for Graph-Based Retrieval-Augmented Generation arXiv:2607.28397v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) over knowledge graphs requires retrievers that can effectively capture both graph structure and semantic information. Recent approaches have explored graph neural network (GNN)-based… 35 Hugging Face Daily Papers research 1mo ago BM25 Wins at Scale: A Scaling Study of Retrieval-Augmented Generation Paradigms Abstract Retrieval-augmented generation (RAG) spans lexical and dense retrieval, graph-based indexing, and agentic search, but these paradigms are usually evaluated on different benchmarks at one corpus size, leaving their accuracy-cost scaling unclear. To bridge this gap, we… 29 Hugging Face Daily Papers research 1mo ago ACE-Data-0: Human-Centric Ambient Capture as Embodied Data Engine Abstract Embodied intelligence faces a fundamental data bottleneck. Models must capture how first-person perception, whole-body motion, dexterous manipulation, object state, sound, and touch evolve together as humans pursue goals over time. Existing datasets fragment this… 24 TechCrunch — AI news-outlet 1mo ago AI hedge fund Situational Awareness may have sold its public portfolio, but it still has its Anthropic shares The former OpenAI researcher’s fund was forced to unwind public equities after leveraged public bets plummeted. But he still has cards to play. 31 llama.cpp releases dev-tools 1mo ago b10194 ggml-cuda: Allow transpose-free gemmv computation ( #26171 ) When matrix's weights are shaped 1xK is leverage a transpose-free computation to use mat_mul_vec_f. Website: https://llama.app macOS/iOS: macOS Apple Silicon (arm64) macOS Apple Silicon (arm64, KleidiAI enabled)… 20 Hugging Face Daily Papers research 1mo ago CADENCE: Closing the Reasoning Gap via Coverage-Adaptive On-Policy Distillation Abstract On-policy knowledge distillation transfers reasoning from large teachers to compact students, but existing approaches suffer three compounding failure modes: (i) cold-start collapse, where a fresh student assigns near-zero mass to teacher-preferred tokens; (ii)… 18 arXiv — Machine Learning research 1mo ago FloDR: An invertible dimensionality reduction method based on a normalising flow arXiv:2607.26278v1 Announce Type: new Abstract: It is common for two-dimensional embeddings of high-dimensional data to be read far beyond what they can support. Distances in and between clusters, the meaning behind empty spaces, and the amount of structure hidden at each point… 22 arXiv — Machine Learning research 1mo ago RAGuard: A Layered Defense Framework for Retrieval-Augmented Generation Systems Against Data Poisoning arXiv:2607.26339v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) systems ground large language models (LLMs) in external corpora, but this reliance exposes them to corpus poisoning: maliciously injected passages that manipulate retrieved evidence. We… 28 arXiv — Machine Learning research 1mo ago ClockRoPE: Random Fourier Rotations for Temporal Routine Modeling arXiv:2607.26369v1 Announce Type: new Abstract: Rotary Position Embedding (RoPE) has been widely adopted in transformer-based large language models. However, its log-linear frequency schedule, originally designed to produce long-term attention decay, limits its adoption in… 38 arXiv — Machine Learning research 1mo ago From Conceptual Hydrologic Models to Conceptually Interpretable Neural Networks: A Snow-Water Mass-Conserving-Perceptron Framework for Discovering Catchment-Scale Precipitation-Storage-Runoff Representations arXiv:2607.26492v1 Announce Type: new Abstract: The Mass-Conserving Perceptron (MCP) establishes a modeling paradigm in which conceptual hydrologic models can be reformulated as physically constrained, conceptually interpretable neural networks. Here, we develop a snow-water MCP… 35 arXiv — Machine Learning research 1mo ago Simultaneous Coverage and Efficiency Guarantee in Online Conformal Prediction arXiv:2607.26577v1 Announce Type: new Abstract: Adaptive conformal inference (ACI) of Gibbs and Cand{\`e}s and its variants are the standard approach to online conformal prediction under distribution shift, but they suffer from three fundamental limitations. First, their… 30 arXiv — Machine Learning research 1mo ago Uncertainty-Guided LLM Semantic Augmentation for Heterogeneous Treatment Effect Estimation arXiv:2607.26599v1 Announce Type: new Abstract: Estimating heterogeneous treatment effects is central to targeted interventions, such as personalized promotions and precision medicine. We focus on the conditional average treatment effect (CATE), a standard estimand for… 6 arXiv — Machine Learning research 1mo ago RAG-HAR+: Towards Cost-Efficient LLM-Based Human Activity Recognition for Edge Deployment arXiv:2607.26631v1 Announce Type: new Abstract: Human Activity Recognition (HAR) from wearable sensors supports applications in healthcare, rehabilitation, fitness tracking, and smart environments. Yet, existing deep learning approaches require dataset-specific training, large… 24 arXiv — NLP / Computation & Language research 1mo ago Robostreet Flow: A Lightweight, Ultra-Low-Drag Electric Tractor and Four-Truck Hybrid Convoy Architecture for Minimum-Cost Point-to-Point Freight arXiv:2607.26250v1 Announce Type: new Abstract: Line-haul trucking costs are dominated by three comparably sized components: energy, driver labor, and equipment. Most efficiency technologies address only one component at a time. This paper presents Robostreet Flow, a freight… 38 arXiv — NLP / Computation & Language research 1mo ago CMT-RAG: Complementary Memory Traces for Multi-turn Multi-hop RAG arXiv:2607.26470v1 Announce Type: new Abstract: Multi-turn information-seeking conversations require both multi-hop reasoning and long-range dependency tracking across turns. However, existing RAG systems typically represent conversational memory as raw dialogue history,… 32 arXiv — NLP / Computation & Language research 1mo ago Which RAG Paradigm Wins at Scale? A Scaling Study of Retrieval-Augmented Generation Paradigms arXiv:2607.26497v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) methods range from lexical and dense retrieval to graph-based indexing and agentic search. They are usually evaluated on different benchmarks at one corpus size, leaving their accuracy-cost… 35 arXiv — NLP / Computation & Language research 1mo ago WikiLoop: Jointly Learning to Build and Navigate Agent-Native Wikis with Downstream Feedback arXiv:2607.26604v1 Announce Type: new Abstract: Knowledge-base construction and querying are typically optimized in isolation: retrieval-augmented agents operate over a fixed, externally maintained index, whereas construction receives no signal from downstream use. We present… 15 arXiv — NLP / Computation & Language research 1mo ago ARC-Encoder: learning compressed text representations for large language models arXiv:2510.20535v2 Announce Type: replace Abstract: Recent techniques such as retrieval-augmented generation or chain-of-thought reasoning have led to longer contexts and increased inference costs. Context compression techniques can reduce these costs, but the most effective… 8 arXiv — NLP / Computation & Language research 1mo ago Ensembling LLM-Induced Decision Trees for Explainable and Robust Error Detection arXiv:2512.07246v3 Announce Type: replace Abstract: Error detection (ED), which aims to identify incorrect or inconsistent cell values in tabular data, is important for ensuring data quality. Recent state-of-the-art ED methods leverage the pre-trained knowledge and semantic… 21 Hacker News — AI on Front Page community 1mo ago The Productivity Mirage Article URL: https://frantic.im/mirage/ Comments URL: https://news.ycombinator.com/item?id=49104335 Points: 216 # Comments: 71 23 r/LocalLLaMA community 1mo ago Bought a 5090 to escape API fees. Ended up building a mini datacenter. Sound familiar? I bought an RTX 5090 last year just to run 27B models natively. I even fine-tuned it with my own data using LoRA, building RAGs and was pretty damn happy with the results at first. But, Q8 quantization 130k context was barely squeezing through. Naturally, I bought two RTX 6000… 37 r/LocalLLaMA community 1mo ago Budget Inference: A GPU for dense models vs. More RAM for MoE models? Hi all, I’m building a budget inference machine primarily for personal use (chat/assistant tasks, possibly some RAG). I'm torn between two hardware paths and would love input from anyone who has actually benchmarked these setups. The Dilemma: Option A (GPU for dense models): Buy… 35 r/MachineLearning community 1mo ago Vendor-agnostic ML inference on production edge devices [R] I work on PostSlate, a video editing tool, and this comes out of our own work. We run ML models on-device, face detection and embedding among other things, which means we can't assume anything about the user's GPU. NVIDIA discrete, AMD, Intel integrated, Apple Silicon, all of… 7 Hugging Face Daily Papers research 1mo ago Temporal-Distance JEPA: Plan-Aware Representation Learning for Latent World Model Predictive Control Abstract Joint-Embedding Predictive Architectures (JEPAs) learn world models by predicting in representation space rather than reconstructing pixels, making them a natural backbone for latent model predictive control from offline demonstration logs. JEPA-style training optimizes… 30 arXiv — NLP / Computation & Language research 1mo ago Temporal-Distance JEPA: Plan-Aware Representation Learning for Latent World Model Predictive Control arXiv:2607.25337v1 Announce Type: new Abstract: Joint-Embedding Predictive Architectures (JEPAs) learn world models by predicting in representation space rather than reconstructing pixels, making them a natural backbone for latent model predictive control from offline… 36 arXiv — NLP / Computation & Language research 1mo ago Detecting Knowledge Inconsistencies Across Text, Tables, and Knowledge Graphs arXiv:2607.25959v1 Announce Type: new Abstract: Wikipedia and Wikidata are widely used for information access, LLM pre-training, and retrieval-augmented generation. Their knowledge is deeply connected but scattered across text, tables, and knowledge graphs. This raises a… 28 Page 9 of 10 · 500 articles ← Newer Older →
