News / #rag Tag Rag 500 articles archived under #rag · RSS Sign in to follow arXiv — Machine Learning research 10d ago A Physics-Chemistry-Informed Neural Network (PCINN) for Real-Time Spatial-ALD Coverage Prediction and Reliable Kinetics Inversion arXiv:2608.00212v1 Announce Type: new Abstract: Spatial atomic layer deposition (SALD) is a leading atmospheric-pressure, high-throughput route to industrial ALD, but design and control are limited by the cost of predicting surface coverage: high-fidelity CFD is far too slow for… 32 arXiv — Machine Learning research 10d ago HP-JEPA: Hierarchical Partitioning for Multi-Resolution Graph Joint-Embedding Predictive Learning arXiv:2608.00491v1 Announce Type: new Abstract: Graph self-supervised learning aims to learn transferable representations from large-scale unlabeled graph data. Joint-embedding predictive architectures (JEPAs) avoid explicit negative-pair construction and raw-input… 19 arXiv — Machine Learning research 10d ago Deep Learning CNN and Recurrence Analysis for Alpha Gamma EEG Biomarkers in Fragile X Syndrome arXiv:2608.00835v1 Announce Type: new Abstract: Fragile X Syndrome (FXS) is a neurodevelopmental disorder caused by reduced expression of fragile X mental retardation protein (FMRP), leading to disrupted synaptic plasticity, cortical hyperexcitability, and impaired network… 37 arXiv — Machine Learning research 10d ago UpliftBench: Revealing Outcome-Regime and Objective Mismatch in Uplift Evaluation arXiv:2608.00915v1 Announce Type: new Abstract: Uplift modeling (conditional-average-treatment-effect estimation) drives personalized targeting, yet published uplift benchmarks frequently disagree on which estimator performs best; we show the disagreement is substantially about… 33 arXiv — Machine Learning research 10d ago Beyond Gene Reconstruction: Learning Cell Representations through Complementary Transcriptomic Views arXiv:2608.00985v1 Announce Type: new Abstract: The rapid growth of single-cell transcriptomic data has enabled the development of foundation models pretrained primarily by reconstructing masked expression values. This objective encourages these models to learn gene dependencies… 35 arXiv — Machine Learning research 10d ago Differentiable Lifting for Topological Neural Networks arXiv:2608.01160v1 Announce Type: new Abstract: Topological neural networks (TNNs) enable leveraging high-order structures on graphs (e.g., cycles and cliques) to boost the expressive power of message-passing neural networks. In turn, however, these structures are typically… 36 arXiv — Machine Learning research 10d ago FedChronos: Federated Fine-Tuning of Time-Series Foundation Models for Privacy-Preserving Commodity Price Forecasting arXiv:2608.01290v1 Announce Type: new Abstract: Time-series foundation models (TSFMs) such as Chronos have demonstrated strong forecasting capabilities across domains, yet adapting them to institutionally fragmented settings, where data cannot be centralized due to regulatory,… 18 arXiv — Machine Learning research 10d ago Conformalized Large Language Models under Configuration Shift arXiv:2608.01460v1 Announce Type: new Abstract: Conformal prediction (CP) is a distribution-free framework for uncertainty quantification that has recently been adapted to large language models (LLMs), providing prediction sets with finite-sample coverage guarantees under… 22 arXiv — Machine Learning research 10d ago Interpretable MEG Decoding of Perceived Speech: Cortical Sources and the Stimulus Features That Drive Retrieval arXiv:2608.01481v1 Announce Type: new Abstract: Short segments of perceived speech can be retrieved from non-invasive magnetoencephalographic (MEG) recordings by deep networks trained with a CLIP-style objective against wav2vec 2.0 audio embeddings. Yet their weights do not map… 38 arXiv — NLP / Computation & Language research 10d ago Averaging Bias: Human Faithfulness Annotations are not Locally Faithful arXiv:2608.00205v1 Announce Type: new Abstract: Evaluation of faithfulness of text summarization treats a model generated summary as faithful only if every of its sentences is supported by the source document: a strict conjunctive rule under which a single unsupported sentence… 29 arXiv — NLP / Computation & Language research 10d ago Cross-Task Dissociation in Frontier Vision-Language Model Theory of Mind arXiv:2608.00261v1 Announce Type: new Abstract: Do frontier vision-language models present a coherent Theory-of-Mind (ToM) profile across tasks, matching the same human reference group, or does that profile fragment from one paradigm to the next? We evaluate a shared panel of… 22 arXiv — NLP / Computation & Language research 10d ago Sixteen models, fewer than two voices: measuring ensemble dispersion where no answer is uniquely correct arXiv:2608.00285v1 Announce Type: new Abstract: Sixteen language models drawn from ten families produced, on average, the semantic diversity of 1.69 distinct formulations of a psychotherapeutic case, against a single-model baseline of 1.43 from one model's own runs. Ensembles… 11 arXiv — NLP / Computation & Language research 10d ago Writing-System-Level Tokenizer Adaptation for Byte-Level BPE arXiv:2608.00582v1 Announce Type: new Abstract: Pretrained byte-level BPE tokenizers can segment underrepresented languages inefficiently. Replacing a tokenizer changes the meaning of nearly every token ID, while vocabulary expansion enlarges the model's embedding and output… 6 arXiv — NLP / Computation & Language research 10d ago Verification Without Sufficiency: Per-Chunk Filtering Fails on Multi-Hop RAG, and Decomposition Repairs It arXiv:2608.00585v1 Announce Type: new Abstract: Verification for retrieval-augmented generation usually scores each retrieved chunk and drops the ones that fail. We show this cannot work for multi-hop questions, and show what does. Per-chunk scoring assumes one chunk is a… 9 arXiv — NLP / Computation & Language research 10d ago TreeProbe : A Tibetan Medicine Benchmark for Cultural Bias in LLMs arXiv:2608.00640v1 Announce Type: new Abstract: Large language models are increasingly viewed as a potential means of mitigating global health inequities, yet their outputs often reflect dominant high-resource medical traditions and provide limited coverage of traditional… 38 arXiv — NLP / Computation & Language research 10d ago Select-And-Extract: A Lightweight Plugin for Retrieval-Augmented Generation arXiv:2608.00658v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) for language model (LM) systems fundamentally has two failure modes: retrieval failure and reading failure. The former fails to recall the right pieces of information from the external corpus,… 35 arXiv — NLP / Computation & Language research 10d ago RAGOCR: Optical Compression of Retrieval-Augmented Text via Visual Representation arXiv:2608.00765v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has become essential for knowledge-intensive question answering, yet scaling RAG pipelines remains challenging due to the prohibitive computational cost of processing lengthy retrieved contexts.… 31 arXiv — NLP / Computation & Language research 10d ago Does Machine "know" interpersonal pragmatics? Evidence from MARBERT's learning of emoji pragmatics in Arabic digital discourse arXiv:2608.01174v1 Announce Type: new Abstract: This study examines Transformer-based models' ability to learn emoji pragmatics in Arabic digital discourse (ADD), providing evidence from MARBERT's behavior with interpersonal pragmatic functions (IPFs). A corpus of 8,504 unique… 19 arXiv — NLP / Computation & Language research 10d ago ACE-GraphRAG: Agentic Context Engineering for Hierarchical GraphRAG arXiv:2608.01269v1 Announce Type: new Abstract: Hierarchical Graph Retrieval-Augmented Generation (GraphRAG) organizes corpus knowledge at multiple levels of granularity, yet fixed context construction may fail to translate these multi-resolution representations into a context… 28 arXiv — NLP / Computation & Language research 10d ago RH-RAG: Trustworthy Long-Form Generation for Privacy-Constrained Settings arXiv:2608.01311v1 Announce Type: new Abstract: Generating long-form content from extensive internal reports remains challenging for organizations operating under strict privacy and security constraints, where proprietary cloud-based LLM APIs are often not viable. While locally… 36 arXiv — NLP / Computation & Language research 10d ago Discriminative Axis, Not Data Volume: What a Contrastive Corpus Teaches an Audio Embedding arXiv:2608.01560v1 Announce Type: new Abstract: Scaling the corpus is the default remedy when a contrastive representation lacks an attribute. We report a case where it does nothing, and identify what does: adding a lexical-speech round to a frozen-base multimodal embedding… 29 arXiv — NLP / Computation & Language research 10d ago DocNavRAG: Document-Structured Graph RAG with Stateful Evidence Construction for Complex Document Question Answering arXiv:2608.01565v1 Announce Type: new Abstract: Answering complex questions over large document collections requires assembling complementary evidence across sections and documents. GraphRAG offers structured retrieval but typically uses fixed traversal, while agentic RAG… 21 arXiv — NLP / Computation & Language research 10d ago RING: Retrieval-Internalized Generation for Continual Large-Scale Knowledge Injection arXiv:2608.01630v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves factuality but adds latency and engineering overhead at serving time. We propose RING (Retrieval-Internalized Generation), a holistic paradigm spanning both architecture and training… 8 Hugging Face Daily Papers research 10d ago UEmbed: Unified Sparse and Dense Multimodal Embeddings Abstract Sparse retrieval underpins modern search systems, from web search to retrieval-augmented generation. Existing work has introduced Learned Sparse Retrieval (LSR) to push beyond exact lexical matching toward richer semantics. Yet LSR has so far remained tied to… 5 OpenAI Python SDK releases dev-tools 10d ago v2.53.0 2.53.0 (2026-08-03) Features api: Add gpt-5.5 and tool name/namespace to Responses types ( #3569 ) ( dd1202d ) Bug Fixes ci: avoid NumPy source builds and duplicate HTTPX coverage ( #3573 ) ( b58332f ) 8 r/LocalLLaMA community 10d ago 'I ran my own benchmarks on it' seems to be pretty common comment around here. How about dedicating a thread for this and sharing? Of course, the concern is that in the end, this thread will be fed into the models' training data, but I feel benchmarking isn't so open and very fragmented.   submitted by   /u/jinnyjuice [link]   [comments] 38 r/MachineLearning community 10d ago ARPL — runtime ISA/topology detection for llama.cpp on ARM (built for Snapdragon 8 Elite) [r] I've been working on this for a while and finally pushed a public version. The problem: llama.cpp runs fine on ARM phones, but it doesn't know anything about the specific chip it's on. Same thread count, same context params, whether you're on a Snapdragon 8 Elite or a… 24 r/LocalLLaMA community 10d ago I CANNOT believe I've got DeepSeek-V4-Flash-0731, a frontier model, running on my home PC. Insane! So this is the stuff of absolute insanity. In less than 20 months we've gone from super expensive cloud models only, to being able to run a Q3 quant of DeepSeek on an Intel Windows PC with a very average 24GB of VRAM. No wonder the big boys are panicking (and yes it's slow as… 10 NVIDIA Developer Blog official-blog 10d ago NVIDIA Vera Storage Benchmarks: Faster Encryption, Compression, Integrity Checking, and Recovery for AI-Native Storage Storage is an active part of every agentic AI workflow. As agents retrieve enterprise knowledge, access persistent memory, reuse key-value (KV) cache data,... 17 Hugging Face Daily Papers research 10d ago SAF-OPD: Stable Advantage Fusion for On-Policy Distillation Abstract Reinforcement learning with verifiable rewards (RLVR) broadcasts a single response-level reward to every token, while on-policy distillation (OPD) scores each token against a stronger teacher for a dense advantage but caps performance at teacher quality and discourages… 8 Hugging Face Daily Papers research 11d ago One Future, Every Robot: Label-Efficient Collective-State Prediction with Decentralized JEPA Abstract Can every robot in a swarm predict the same future collective state from only local observations and bandwidth-limited messages? We formulate this as decentralized shared-state prediction and introduce Collective-State JEPA (CS-JEPA), a recurrent joint-embedding… 29 r/LocalLLaMA community 11d ago I benchmarked classic vector RAG vs Google's new OKF format vs both combined — same corpus, same 7 questions, all local (Ollama + ChromaDB) Google Cloud published OKF (Open Knowledge Format) on June 12th — a spec for storing curated knowledge as a directory of markdown files with YAML frontmatter. One concept per file, linked to each other, with an index.md for progressive disclosure. The only required field is… 7 arXiv — Machine Learning research 11d ago Guarantees on Dynamical System Distinguishability for LLM Token Generation arXiv:2607.28667v1 Announce Type: new Abstract: Recent work has shown that classifying large language models (LLMs)' responses can be distinguished by modeling token embeddings as trajectories of a black-box dynamical system (DS) and comparing prediction residuals of two DSs.… 28 arXiv — Machine Learning research 11d 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 11d 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 11d 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 11d 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 11d 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 11d 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 11d 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 11d 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 11d 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 12d 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 13d 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 14d 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 14d 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 14d 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 14d 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 14d 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 14d 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 Page 4 of 10 · 500 articles ← Newer Older →
