News / #rag Tag Rag 500 articles archived under #rag · RSS Sign in to follow arXiv — Machine Learning research 12d ago Robust and Interpretable Adaptation of Equivariant Materials Foundation Models via Sparsity-promoting Fine-tuning arXiv:2606.18691v1 Announce Type: new Abstract: Pre-trained materials foundation models, or machine learning interatomic potentials, leverage general physicochemical knowledge to effectively approximate potential energy surfaces. However, they often require domain-specific… 10 arXiv — NLP / Computation & Language research 12d ago SproutRAG: Attention-Guided Tree Search with Progressive Embeddings for Long-Document RAG arXiv:2606.18381v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) systems must balance retrieval granularity with contextual coherence, a challenge that existing methods address through LLM-guided chunking, single-level context expansion, or hierarchical… 23 arXiv — NLP / Computation & Language research 12d ago MCompassRAG: Topic Metadata as a Semantic Compass for Paragraph-Level Retrieval arXiv:2606.18508v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) systems depend critically on how documents are chunked and searched. Fine-grained chunks can improve retrieval precision but expand the search space, increasing latency and cost; larger chunks… 28 arXiv — NLP / Computation & Language research 12d ago PragReST: Self-Reinforcing Counterfactual Reasoning for Pragmatic Language Understanding arXiv:2606.18624v1 Announce Type: new Abstract: Natural language understanding often depends on meanings that are implied rather than explicitly stated, requiring pragmatic reasoning. Despite strong performance on math and logical reasoning, large language models (LLMs) still… 6 arXiv — NLP / Computation & Language research 12d ago Morpheus: A Morphology-Aware Neural Tokenizer and Word Embedder for Turkish arXiv:2606.18717v1 Announce Type: new Abstract: Turkish is agglutinative: meaning is carried by morphemes, yet the subword tokenizers that drive modern language models split words by corpus statistics, fragmenting semantically loaded suffixes and -- in the case of WordPiece and… 27 arXiv — NLP / Computation & Language research 12d ago Beyond Tokenization: Direct Timestep Embedding and Contrastive Alignment for Time-Series Question Answering arXiv:2606.18986v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have given rise to time-series question answering (TSQA), which formulates time-series analysis as natural-language question answering. However, directly feeding raw numerical series… 10 arXiv — NLP / Computation & Language research 12d ago Compact Geometric Representations of Hierarchies arXiv:2606.18520v1 Announce Type: cross Abstract: Computing geometric representations of data is a cornerstone of modern machine learning, typically achieved by training dual encoders which map queries and documents into a shared embedding space. Recent work of You et al.… 25 TechCrunch — AI news-outlet 12d ago NEA’s Tiffany Luck says enterprises are still figuring out their AI ROI Tokenmaxxing was the hottest trend in Silicon Valley earlier this year, with CEOs encouraging employees to push AI usage as far as it would go. Then the bill came due. Uber reportedly blew through its annual AI budget in a few months, some companies… 7 Hugging Face Daily Papers research 12d ago Beyond Scalar Distances: Semantic Attribute Gradients from Frozen MLLMs for Visual Embeddings Abstract SAGA framework uses multimodal large language models to provide attribute-aware supervision for vision encoders through Group Relative Policy Optimization, improving zero-shot image retrieval performance. Generated by Qwen/Qwen2.5-Coder-32B-Instruct Vision encoders for… 21 TechCrunch — AI news-outlet 12d ago NEA’s Tiffany Luck on AI IPOs, personal agents, and the ROI reckoning Tokenmaxxing was the hottest trend in Silicon Valley earlier this year, with CEOs encouraging employees to push AI usage as far as it would go. Then the bill came due. Uber reportedly blew through its annual AI budget in a few months, some companies… 23 r/MachineLearning community 12d ago ACL 2026 first author with weak GPA. How should I approach PhD applications? [D] Hi everyone, I have a fairly weak undergraduate: a 3.3/5 GPA in Computer Engineering from an average Nigerian university. For my Master's, I studied Artificial Intelligence at an average European university, where I finished with an 8/10 GPA. A condensed version of my Master's… 17 Hugging Face official-blog 12d ago From the Hugging Face Hub to robot hardware with Strands Agents and LeRobot Back to Articles a]:hidden"> From the Hugging Face Hub to robot hardware with Strands Agents and LeRobot Enterprise Article Published June 17, 2026 Upvote 4 Sundar Raghavan rsundaraws amazon Cagatay Cali cagataydev amazon A walkthrough of the LeRobot integration in Strands… 28 arXiv — Machine Learning research 13d ago Constrained Diffusion Models with Primal-Dual Inference arXiv:2606.17192v1 Announce Type: new Abstract: This paper develops constrained diffusion models with primal-dual inference (PDI) to sample from optimal distributions of entropy-regularized optimization problems with \emph{average} constraints. We formalize constrained sampling… 19 arXiv — Machine Learning research 13d ago The Discrete-Log Clock: How a Transformer Learns Modular Multiplication arXiv:2606.17399v1 Announce Type: new Abstract: When small transformers grok modular multiplication, prior work reports that the learned embedding has a "dense" Fourier spectrum requiring all frequencies. This contrasts with modular addition, where only a sparse set of key… 11 arXiv — Machine Learning research 13d ago Amortized Probabilistic Retrieval of Atmospheric CO2 from OCO-2 Spectra Using Deep Learning with Laplace Approximations and Normalizing Flows arXiv:2606.17413v1 Announce Type: new Abstract: Space-based monitoring of atmospheric carbon dioxide (CO2) is essential for constraining the global carbon budget. NASA's Orbiting Carbon Observatory-2 (OCO-2) estimates column-averaged dry-air mole fractions of CO2 (XCO2) using… 12 arXiv — Machine Learning research 13d ago PIVOT: Bridging Black-Scholes Implied-Volatility and Price Objectives via Differentiable J\"ackel Operator arXiv:2606.17065v1 Announce Type: cross Abstract: Modern option-learning systems operate in two coordinates: price space, where markets quote and no-arbitrage constraints are most naturally enforced, and implied volatility (IV) space, where volatility surfaces are smoothed,… 13 arXiv — NLP / Computation & Language research 13d ago PromptMN: Pseudo Prompting Language arXiv:2606.17164v1 Announce Type: new Abstract: Prompting has become the primary interface between humans and generative AI, yet many natural language prompts remain fragile: roles, goals, constraints, and expected outputs are often buried in prose or left implicit. In agentic… 13 arXiv — NLP / Computation & Language research 13d ago Examining the Limits of Word2Vec with Toki Pona arXiv:2606.17299v1 Announce Type: new Abstract: Word2Vec's effectiveness at generating semantic embeddings has been widely validated, yet it has been tested almost exclusively on languages with large vocabulary inventories. This study examines whether Word2Vec can successfully… 30 arXiv — NLP / Computation & Language research 13d ago MODE-RAG: Manifold Outlier Diagnosis and Energy-based Retrieval-Augmented Generation Evaluation arXiv:2606.17449v1 Announce Type: new Abstract: While Multimodal Retrieval-Augmented Generation (M-RAG) enhances Large Vision-Language Models, it remains highly susceptible to cross-modal hallucinations, causal fabrications, and sycophancy. Furthermore, existing mitigation… 38 arXiv — NLP / Computation & Language research 13d ago HistoRAG: Embedding Historical Methodology in Retrieval-Augmented Generation Through Critical Technical Practice arXiv:2606.18103v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) is the prevailing architecture for grounding language model outputs in external evidence, yet its dominant evaluation paradigms and default configurations remain oriented toward factual… 8 arXiv — NLP / Computation & Language research 13d ago Non-negative Elastic Net Decoding for Information Retrieval arXiv:2606.17910v1 Announce Type: cross Abstract: Dense retrieval has become the dominant paradigm in information retrieval, in which each document is scored against a query by the inner product of their vector embeddings, and the top-$k$ documents by score are retrieved for… 33 arXiv — NLP / Computation & Language research 13d ago Reading between the Lines: Leveraging Large Language Models for Global Dementia and Depression Assessment from Clinical Interviews arXiv:2606.18019v1 Announce Type: cross Abstract: Dementia and depression are the most prevalent neuropsychiatric disorders in geriatric populations, and their overlapping symptoms pose major challenges for differential diagnosis. In this study, we investigate open-weights Large… 30 arXiv — NLP / Computation & Language research 13d ago LegalHalluLens: Typed Hallucination Auditing and Calibrated Multi-Agent Debate for Trustworthy Legal AI arXiv:2606.18021v1 Announce Type: cross Abstract: AI systems deployed in legal workflows hallucinate at rates that aggregate metrics report at ~52%, but this average conceals where errors concentrate and in which direction they run, leaving compliance officers without an… 4 Hugging Face Daily Papers research 13d ago ACE-Ego-0: Unifying Egocentric Human and Robotic Data for VLA Pretraining Abstract A unified Vision-Language-Action pretraining framework leverages heterogeneous data sources including human egocentric videos and robot trajectories through a reliability-aware training approach that improves performance on embodied AI tasks. Generated by… 6 Hacker News — AI on Front Page community 13d ago Why is Meta destroying its engineering organization? Article URL: https://newsletter.pragmaticengineer.com/p/why-is-meta-destroying-its-engineering Comments URL: https://news.ycombinator.com/item?id=48558045 Points: 224 # Comments: 143 23 Hugging Face Daily Papers research 13d ago You Don't Need Strong Assumptions: Visual Representation Learning via Temporal Differences Abstract Temporal Difference in Vision (TDV) presents a novel self-supervised learning approach for video data that eliminates traditional inductive biases by leveraging causal relationships between past and future frames. Generated by Qwen/Qwen2.5-Coder-32B-Instruct Progress in… 30 TechCrunch — AI news-outlet 13d ago SpaceX is public: Everything you need to know post-IPO TechCrunch has followed SpaceX's start, struggles, and successes from the early days. And we're here for what happens next too. This package of SpaceX IPO coverage includes who stands to win (and maybe some who won't), pre-IPO deals, and what's tucked inside its S-1 registration… 28 Hugging Face Daily Papers research 13d ago MVEB: Massive Video Embedding Benchmark Abstract A large-scale video embedding benchmark evaluates diverse models across multiple video understanding tasks, revealing that different model architectures excel in specific domains and demonstrating the nuanced impact of audio on performance based on dataset… 7 Stratechery (Ben Thompson) community 13d ago Fox Buys Roku, The Problem With Fox’s Smart Strategy, Streaming That Works The market hates Fox's acquisition of Roku, but the company is trading extraction from rights holders for leverage as a renter. 20 llama.cpp releases dev-tools 14d ago b9664: sycl: support reordered Q4_K/Q5_K/Q6_K MoE MUL_MAT_ID (#24452) sycl: support reordered Q4_K and Q5_K MoE MUL_MAT_ID Extend reordered-weight handling to fused MoE MUL_MAT_ID for Q4_K and Q5_K expert tensors and add Q5_K reordered DMMV coverage. Unsupported 3D reorder cases now fall back instead of aborting. sycl: extend MoE reorder to Q6_K… 21 Hugging Face Daily Papers research 14d ago Geometric Action Model for Robot Policy Learning Abstract A geometric action model leverages pretrained geometric foundation models to enable language-conditioned manipulation policies with improved accuracy, robustness, and efficiency in 3D physical environments. Generated by Qwen/Qwen2.5-Coder-32B-Instruct Generalist robot… 21 arXiv — Machine Learning research 14d ago Policy Regret for Embedding Model Routing: Contextual Bandits with Low-Rank Experts arXiv:2606.14929v1 Announce Type: new Abstract: Modern recommendation systems increasingly rely on dynamically routing diverse queries to multiple embedding models. Despite its practical significance, this problem remains poorly understood under realistic conditions like… 18 arXiv — Machine Learning research 14d ago Leveraging Physiological Signals to Predict Exam Outcomes with Machine Learning arXiv:2606.14960v1 Announce Type: new Abstract: This study investigates the application of machine learning models to predict exam outcomes using physiological data collected during examination sessions. Physiological stress indicators, including electrodermal activity, heart… 15 arXiv — Machine Learning research 14d ago TriAdReview: Triangular Adversarial Review Architecture for Multi-Model Technical Document Generation arXiv:2606.15074v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used for technical document generation, yet single-model outputs often suffer from over-engineering, security blind spots, and incomplete coverage. We propose TriAdReview, a triangular… 24 arXiv — Machine Learning research 14d ago Constitutional Value Potentials: reading and steering internal priority margins in language models arXiv:2606.15420v1 Announce Type: new Abstract: A constitution tells a language model what to value, but little tells us whether it does. Adherence is judged from outputs, and output evidence is most fragile on value conflicts, where what matters is not which value a model… 20 arXiv — Machine Learning research 14d ago Unsupervised Learning for Missing Modalities in Multimodal Learning arXiv:2606.15743v1 Announce Type: new Abstract: This paper addresses the missing-modality challenge in multi-modal learning by introducing Unsupervised Learning for Missing Modalities in Multi-Modal Learning (UL4M4), a flexible framework that imputes missing feature embeddings… 35 arXiv — Machine Learning research 14d ago Bayesian Networks with Latent Time Embedding for Stage-Aware Causal Modeling of Alzheimer's Disease Progression arXiv:2606.15784v1 Announce Type: new Abstract: Alzheimer's disease (AD) progression is often described through the amyloid-tau-neurodegeneration, or AT(N), cascade. However, most longitudinal models represent this cascade either as a fixed sequence of biomarkers or as a… 5 arXiv — NLP / Computation & Language research 14d ago SAG: SQL-Retrieval Augmented Generation with Query-Time Dynamic Hyperedges arXiv:2606.15971v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) offers an effective approach for large language models to access external knowledge. However, existing methods rely on dense similarity retrieval and face inherent limitations in handling… 9 arXiv — NLP / Computation & Language research 14d ago Formalize Once, Edit the Rest: Efficient Lean-Based Answer Selection for Math Reasoning arXiv:2606.15972v1 Announce Type: new Abstract: With large language models (LLMs) increasingly applied to mathematical reasoning, formal proof assistants such as Lean can be leveraged to verify reasoning outputs with machine-checkable rigor, enabling use cases such as answer… 30 arXiv — NLP / Computation & Language research 14d ago Who Should Lead Decoding Now? Tracking Reliable Trajectories for Ensembling Masked Diffusion Language Models arXiv:2606.16281v1 Announce Type: new Abstract: Masked Diffusion Language Models (MDLMs) have emerged as a distinct paradigm for sequence generation. As MDLMs become diverse in capabilities and knowledge coverage, an important question is how to combine their knowledge. Toward… 27 arXiv — NLP / Computation & Language research 14d ago PathRouter: Aligning Rewards with Retrieval Quality in Agentic Graph Retrieval-Augmented Generation arXiv:2606.16409v1 Announce Type: new Abstract: Agentic GraphRAG trains language-model agents to iteratively retrieve and reason over graph-structured evidence, enabling more accurate and context-aware decision-making by efficiently navigating complex information networks.… 30 arXiv — NLP / Computation & Language research 14d ago Lost at the End: Primacy Bias in Multimodal Retrieval-Augmented Question Answering arXiv:2606.16494v1 Announce Type: new Abstract: Knowledge-based visual question answering (KB-VQA) lets vision-language systems answer questions that exceed their parametric knowledge by conditioning a reader on passages retrieved from a Wikipedia-scale knowledge base. In… 30 Hugging Face Daily Papers research 14d ago Retrieve, Don't Retrain: Extending Vision Language Action Models to New Tasks at Test Time Abstract Retrieval-augmented vision-language-action policies eliminate per-task fine-tuning costs by using pre-trained models with indexed demonstrations, enabling efficient cross-embodiment generalization and task adaptation. Generated by Qwen/Qwen2.5-Coder-32B-Instruct… 26 Hugging Face Daily Papers research 14d ago UniDDT: Unifying Multimodal Understanding and Generation with Decoupled Diffusion Transformer Abstract UniDDT addresses key challenges in unified multimodal models by leveraging a Noisy ViT encoder and LLM for semantic encoding while using separate diffusion decoders to balance visual understanding and generation tasks. Generated by Qwen/Qwen2.5-Coder-32B-Instruct… 12 r/MachineLearning community 14d ago Cleo: trying to fit full analyst behavior in a 2B model [P] Hello all! Half of all industrial "chatbots" are just text-to-SQL models in a trenchcoat (and the other half RAG!). I wanted to explore just how small you could make these models if you trained, evaluated, and ran inference in the exact same structured harness, leading to Cleo:… 4 TechCrunch — AI news-outlet 14d ago SpaceX is public: Everything you need to know post-IPO TechCrunch has followed SpaceX's start, struggles, and successes from the early days. And we're here for what happens next too. This package of SpaceX IPO coverage includes who stands to win (and maybe some who won't), pre-IPO deals, and what's tucked inside its S-1 registration… 34 r/MachineLearning community 14d ago Concept-Vector: A design framework for human-interpretable word embeddings [P] This project distills a model's word embeddings into human-interpretable "concept-vectors", i.e. vectors in which each component tracks concerns like semantics, syntax, and even statistics potentially, while associating each component with a human readable and human definable… 37 arXiv — Machine Learning research 15d ago Attention-Based Estimation of the Individual Treatment Benefit Probability under Dose Variation arXiv:2606.13821v1 Announce Type: new Abstract: Estimating the probability that a treatment outperforms a control for an individual patient, called the Individual Probability of Treatment Benefit (IPTB), offers a clinically intuitive alternative to population-average metrics.… 36 arXiv — Machine Learning research 15d ago A Stationarity-and-Coupling Criterion for Training-Free Time-Lagged Spectral Embeddings of Multivariate Time Series arXiv:2606.13823v1 Announce Type: new Abstract: We study training-free fixed-length descriptors for multivariate time series and ask not merely whether such a descriptor performs well, but when it can be expected to work at all. Our object of study is $D(\tau)$, built from a… 15 arXiv — Machine Learning research 15d ago Lyapunov-Based Sample Complexity Analysis for Weakly-Coupled MDPs arXiv:2606.14095v1 Announce Type: new Abstract: We study the sample complexity of learning in average-reward weakly-coupled Markov decision processes (WCMDPs) and Restless Bandits (RBs) under a generative model. Naive reduction to a tabular MDP leads to high complexity bounds as… 29 Page 4 of 10 · 500 articles ← Newer Older →
