News / #rag Tag Rag 500 articles archived under #rag · RSS Sign in to follow arXiv — NLP / Computation & Language research 20d ago Skill-RAG: Failure-State-Aware Retrieval Augmentation via Hidden-State Probing and Skill Routing arXiv:2604.15771v4 Announce Type: replace Abstract: Retrieval-Augmented Generation (RAG) has emerged as a foundational paradigm for grounding large language models in external knowledge. While adaptive retrieval mechanisms have improved retrieval efficiency, existing approaches… 31 Hugging Face Daily Papers research 20d ago Douyin Multimodal Embedding Model Technical Report Abstract Multimodal representation learning is a cornerstone of modern AI. By encoding multimodal queries and targets into vectors, it powers industrial search and recommendation and underpins modern agents. Real-world platforms with complex modalities and massive-scale content,… 36 r/LocalLLaMA community 21d ago Best Embedding + Reranking Model What Local Embedding + Reranking Models are you guys running for RAG? I went down this rabbit hole because I wanted a Embedding Model + Reranker for a Translation Memory Server. Essentially, given X phrase/word/sentence/paragraph in English, can it find a similar… 26 r/LocalLLaMA community 22d ago Anyone else amped up over Qwen 3.8? I’ve been using 3.6 27B Q4, and that quant is fast on an M5. The code has been average, but consistently “good enough.” And, after a year, I can see home LLMs being served at home much like streaming music was introduced. A simple browser extension and all your queries go… 14 Hugging Face Daily Papers research 22d ago FactorJEPA: Factorizing Monolithic Futures into Layout-Agent-Interaction Channels for Crowded and Chaotic Global South Urban Worlds Abstract World models have attracted significant attention for their ability to capture and predict the structure and dynamics of the physical world. In this emerging landscape, Joint Embedding Predictive Architectures (JEPA) offer a particularly compelling direction. We study a… 29 llama.cpp releases dev-tools 23d ago b10306 sycl: *glu flat path ( #26354 ) tests: add SWIGLU perf cases perf mode had no GLU coverage. Adds SWIGLU at 17408 columns, 512 and 2048 tokens, f16 and f32, with the operands both fused and split. sycl: consolidate fused-GLU kernels They differed only in which op_* they called,… 14 Hugging Face Daily Papers research 23d ago Interpretable MEG Decoding of Perceived Speech: Cortical Sources and the Stimulus Features That Drive Retrieval 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 onto electrophysiological quantities,… 20 Hugging Face Daily Papers research 23d ago Task-Conditional Flow Matching for Balanced Multilingual Text Embedding Adaptation Abstract Multilingual text embedding models are commonly adapted using a single training objective across diverse tasks, despite different tasks requiring fundamentally different optimization strategies. We introduce Task-Conditional Flow Matching (TCFM), a multilingual… 33 Hugging Face Daily Papers research 23d ago Teaching Nemotron Greek: Mining a Corpus, Adapting Retrieval, and Grounding Generation for Modern Greek across Specialist Domains Abstract Modern Greek is absent from NVIDIA's Nemotron retrieval models and from major multilingual retrieval benchmarks, despite being important for retrieval-augmented generation (RAG) in legal, energy, financial, and medical applications. We present an end-to-end adaptation… 5 arXiv — Machine Learning research 23d ago PPDL: LLM-Based Flows as Probabilistic Programs arXiv:2608.05234v1 Announce Type: new Abstract: Building reliable applications that leverage large language models (LLMs) remains a significant challenge. While LLMs offer impressive capabilities across diverse tasks, their outputs often lack accuracy and provide no clear… 10 arXiv — Machine Learning research 23d ago Perturbation Sensitivity at Convergence: A Simple Signal for Identifying Spuriously Correlated Samples arXiv:2608.05419v1 Announce Type: new Abstract: Models trained by empirical risk minimization on data containing spurious correlations achieve high average accuracy while failing on subpopulations where the correlation does not hold. Existing methods for identifying the affected… 17 arXiv — Machine Learning research 23d ago IFlowNets: Extending Generative Samplers to Learn Strategies in Incomplete Information Games arXiv:2608.05422v1 Announce Type: new Abstract: While many algorithms blend reinforcement learning (RL) with counterfactual regret (CFR) methods to leverage tradeoffs in computational speed and performance, there are fewer investigations into generative sampling frameworks in… 38 arXiv — Machine Learning research 23d ago Align-RAG: Alignment Is All You Need for TSFM In-Context Learning arXiv:2608.05571v1 Announce Type: new Abstract: Retrieval-augmented forecasting promises to adapt frozen Time Series Foundation Models (TSFMs) to new domains without fine-tuning, but recent methods typically rely on learned fusion modules, i.e., trained adapters that merge… 11 arXiv — Machine Learning research 23d ago BioM-JEPA: joint-embedding prediction of graph-connected gene blocks in single cells arXiv:2608.05928v1 Announce Type: new Abstract: Single-cell transcriptomes are sparse observations of coordinated biological programmes, yet most self-supervised models learn by reconstructing individual genes. Here we present BioM-JEPA, a joint-embedding predictive architecture… 7 arXiv — Machine Learning research 23d ago How Far Do Simple Transformations Translate Across Text Embedding Models? arXiv:2608.05980v1 Announce Type: new Abstract: We investigate whether simple transformations can translate representations across heterogeneous text embedding models. Understanding how independently trained models organize semantic information is an enabler for AI-to-AI latent… 38 arXiv — Machine Learning research 23d ago Dynamic Graph Prompting via Topology-Routed Mixed-Curvature Experts arXiv:2608.06031v1 Announce Type: new Abstract: Dynamic graph prompting freezes a pre-trained temporal backbone and adapts it to label-scarce downstream tasks using lightweight prompts. However, existing methods operate within a single, fixed embedding space. In this work, we… 4 arXiv — NLP / Computation & Language research 23d ago Where Privacy Risk Lives in English-Source Multilingual RAG: A Stage-Decomposed Audit Across Five Query Languages arXiv:2608.05163v1 Announce Type: new Abstract: A common assumption holds that switching to a non-English language makes a multilingual RAG system easier to attack for personal information. We test this on an English-source synthetic-PII corpus with five query languages and a… 31 arXiv — Machine Learning research 23d ago DoctorAgents: an agentic framework to iteratively refine AutoML pipeline for small clinical temporal data arXiv:2608.05375v1 Announce Type: cross Abstract: Clinical machine learning (ML) has the potential to support high-stakes medical decision-making, but reliable deployment is often constrained by scarce, heterogeneous, and temporal complexity. Developing effective ML pipelines… 14 arXiv — NLP / Computation & Language research 23d ago Universal Pathologies, Conditional Consequences: A Triple-Robustness Analysis of RAG for Multi-Hop Traceability arXiv:2608.05153v1 Announce Type: new Abstract: GraphRAG underperforms vector RAG on citation precision in many reports, but where and why have remained corpus-bound. We present a triple-robustness analysis that holds the retrieval architecture fixed and varies three orthogonal… 27 arXiv — NLP / Computation & Language research 23d ago CNM-BERT: A Drop-In Structural Embedding for Chinese Characters via Ideographic Description Sequences arXiv:2608.05167v1 Announce Type: new Abstract: Token-based encoders like BERT treat Chinese characters as atomic identifiers, ignoring their recursive orthographic structure. Consequently, models rely on contextual co-occurrence, degrading performance on rare and… 29 arXiv — NLP / Computation & Language research 23d ago Where Models Converge and Humans Diverge: A Coverage Framework for Distributional Pluralism in Open-Ended Generation arXiv:2608.05576v1 Announce Type: new Abstract: When a large language model (LLM) writes Harry Potter fanfiction, it reliably produces fundamental elements of the Hogwarts universe, such as recognizable places and characters. Human-written Harry Potter fanfictions, however,… 30 arXiv — NLP / Computation & Language research 23d ago Sparse Mutual Information Graph Averaging for Improving Random Indexing Embeddings arXiv:2608.05724v1 Announce Type: new Abstract: Sparse word embedding pipelines can avoid dense co-occurrence matrix materialization, dense factorization, and gradient training while still relying on sparse global corpus statistics. This paper studies Random Indexing (RI)… 8 arXiv — NLP / Computation & Language research 23d ago Task-Conditional Flow Matching for Balanced Multilingual Text Embedding Adaptation arXiv:2608.05785v1 Announce Type: new Abstract: Multilingual text embedding models are commonly adapted using a single training objective across diverse tasks, despite different tasks requiring fundamentally different optimization strategies. We introduce Task-Conditional Flow… 5 arXiv — NLP / Computation & Language research 23d ago Mapping Similarity Spaces across Embedding Models with Synthetic Query Probing arXiv:2608.05857v1 Announce Type: new Abstract: Retrieval-Augmented Generation systems rely on similarity scores to retrieve relevant content, yet scores are not directly comparable across embedding models due to differing geometric properties, complicating model migration and… 4 arXiv — NLP / Computation & Language research 23d ago Beyond Sequence Order: Syntax-Informed Positional Embeddings for Transformers arXiv:2608.06111v1 Announce Type: new Abstract: Positional embeddings (PE) in Transformers encode token distance and order but are largely agnostic to \textit{syntactic structure}. We introduce \textbf{S}yntax-\textbf{i}nformed \textbf{P}ositional \textbf{E}mbeddings… 15 arXiv — NLP / Computation & Language research 23d ago NeSy-RAG: Neuro-Symbolic RAG for Explainable Question Answering arXiv:2608.06292v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves question answering by grounding large language models (LLMs) in external knowledge such as text corpora. However, its reasoning process remains largely opaque: intermediate reasoning… 9 arXiv — NLP / Computation & Language research 23d ago Agentic Nesting: A New Methodology for Existing Enterprise Application Integration and Services arXiv:2608.05159v1 Announce Type: cross Abstract: Enterprise operations extensively rely on multiple heterogeneous business systems and information applications, which also result in severe data silos and process fragmentation. Enterprises have invested considerable financial… 36 arXiv — NLP / Computation & Language research 23d ago Beyond Top-K: Replacing Black-Box Retrieval with Interpretable Agentic Operations arXiv:2608.06305v1 Announce Type: cross Abstract: Retrieval-augmented generation over long documents is dominated by one design: chunk the text, embed the chunks, and surface the top-k nearest neighbours of the query. We argue that for an important class of documents --… 5 arXiv — NLP / Computation & Language research 23d ago Building Open-Retrieval Conversational Question Answering Systems by Generating Synthetic Data and Decontextualizing User Questions arXiv:2507.04884v2 Announce Type: replace Abstract: We consider open-retrieval conversational question answering (OR-CONVQA), an extension of question answering where system responses need to be (i) aware of dialog history and (ii) grounded in documents (or document fragments)… 4 Hugging Face Daily Papers research 24d ago Lossless Tensor Compression as Program Synthesis Abstract Model checkpoints are growing in both number and size, which makes archival, transfer, and deployment increasingly costly. General-purpose compressors can reduce storage requirements but ignore tensor structure, whereas existing tensor-specific compressors rely on fixed… 4 Hugging Face Daily Papers research 24d ago GDPevo: Evaluating Agent Self-Evolution on Real Business Tasks Abstract Agent self-evolution updates an agent's persistent state from prior experience and reuses it to solve related tasks more effectively. Evaluating self-evolution is difficult: existing benchmarks provide limited coverage of economically valuable task domains, do not… 17 arXiv — Machine Learning research 24d ago SJEPA: Learning Elegant Latent Dynamics with Hybrid Symbolic-Neural Predictors arXiv:2608.04060v1 Announce Type: new Abstract: Joint-embedding predictive architectures learn abstract states by predicting target embeddings from context embeddings, but their transition models are typically opaque neural maps. We introduce SJEPA, a reconstruction-free JEPA… 38 arXiv — Machine Learning research 24d ago Adaptive Finite-Budget Training for CVaR Risk-Aware Q-Learning arXiv:2608.04305v1 Announce Type: new Abstract: Risk-aware Q-learning (RaQL) provides a model-free, two-timescale estimator for dynamic risk objectives, but its finite-budget behavior remains fragile: fixed inner-loop hyperparameters can produce unstable value estimates,… 15 arXiv — Machine Learning research 24d ago A 6G Integrated Sensing and Communication Framework for Railway Intrusion Detection and Collision Prediction arXiv:2608.04710v1 Announce Type: new Abstract: Integrated Sensing and Communication (ISAC) combines sensing and communication to efficiently utilize wireless resources and is emerging as a key paradigm for next-generation wireless networks. By leveraging the wide bandwidth,… 5 arXiv — NLP / Computation & Language research 24d ago Leveraging Machine Learning to Gain Insights on Quantum Thermodynamic Entropy arXiv:2305.06177v1 Announce Type: cross Abstract: We present a thermodynamic analysis of a quantum engine that uses a single quantum particle as its working fluid, inspired by Szilard's classical single-particle engine. Our design is modeled after the classically-chaotic Szilard… 31 arXiv — NLP / Computation & Language research 24d ago Eliciting Intrinsic Hallucinations in LLMs via Semantically Equivalent Adversarial Attacks arXiv:2608.04286v1 Announce Type: new Abstract: Large language models (LLMs) are often used in conjunction with external knowledge sources to improve their factual accuracy and decrease hallucinations, through methods such as Retrieval-Augmented Generation (RAG). However, these… 23 arXiv — NLP / Computation & Language research 24d ago Pun Intended: Multi-Agent Translation of Wordplay with Contrastive Learning and Phonetic-Semantic Embeddings arXiv:2608.04311v1 Announce Type: new Abstract: Translating wordplay across languages has long challenged both professional translators and machine translation systems. We investigate three approaches to translating puns from English to French by combining large language models… 25 arXiv — NLP / Computation & Language research 24d ago D$^2$F-ReAG: Dynamic Decomposition and Filtering for Multi-Hop Reasoning-Augmented Generation arXiv:2608.04444v1 Announce Type: new Abstract: Large language models (LLMs) often generate inaccurate answers due to their reliance on static internal knowledge. Retrieval-augmented generation (RAG) addresses this limitation by integrating external knowledge and excelling at… 29 arXiv — NLP / Computation & Language research 24d ago The Personalization Mirage: How LLMs Fabricate User Profiles, and Why Self-Monitoring Misleads arXiv:2608.04570v1 Announce Type: new Abstract: Personalized LLMs with persistent memory are increasingly deployed, yet the faithfulness of their user models remains unexamined. We study over-inference (OI): the phenomenon where LLMs fabricate user attributes beyond what… 16 arXiv — NLP / Computation & Language research 24d ago InsightEmb: Learning Action-Intent Embeddings for Agentic Insight Retrieval arXiv:2608.04761v1 Announce Type: new Abstract: Self-improving agents accumulate reusable insights from prior trajectories, making retrieval increasingly important for turning accumulated experience into actionable guidance. At each decision step, retrieving the right insight… 18 arXiv — NLP / Computation & Language research 24d ago DeepInvert: Semi-Supervised Embedding Inversion Against Obfuscated Language Models arXiv:2608.04477v1 Announce Type: cross Abstract: Cloud-based language model services routinely process prompts containing sensitive information. Obfuscation-based defenses---including ObfusLM, SentinelLMs, TextObfuscator, and DPNR---mitigate this risk by transforming prompt… 25 arXiv — NLP / Computation & Language research 24d ago CARVE: Cross-Slice Anisotropic Reallocation of Visual Evidence for Efficient 3D Medical Volume Understanding arXiv:2608.04515v1 Announce Type: cross Abstract: Slice-based MLLMs leverage mature 2D encoders by representing 3D volumes as sequences of 2D slices. However, this slice-wise formulation produces thousands of visual tokens that burden the LLM backbone, many of which capture… 8 Hugging Face Daily Papers research 24d ago BridgeVLA++: A Data-Efficient, Generalizable, and Memory-Augmented Vision-Language-Action Framework for 3D Manipulation Abstract Leveraging pre-trained vision-language models (VLMs) to construct vision-language-action (VLA) models has emerged as a promising paradigm for 3D robot manipulation. However, existing 3D VLA methods remain data-hungry, exhibit limited generalization under distribution… 4 Hugging Face Daily Papers research 24d ago The Personalization Mirage: How LLMs Fabricate User Profiles, and Why Self-Monitoring Misleads Abstract Personalized LLMs with persistent memory are increasingly deployed, yet the faithfulness of their user models remains unexamined. We study over-inference (OI): the phenomenon where LLMs fabricate user attributes beyond what evidence supports. We introduce MirageBench,… 29 Hugging Face Daily Papers research 25d ago ChronoLens: Measuring Language Change Across Time, Languages, and Linguistic Levels Abstract Historical language change affects morphology, syntax, semantics, and pragmatics, yet computational studies typically examine these levels with incompatible representations and therefore cannot determine whether they evolve together across languages. We address this… 10 Hugging Face Daily Papers research 25d ago Better, Stronger, Faster, and Broader: Structured All-Mask Prediction for MLLM-Based Segmentation Abstract MLLM-based segmentation faces a core segmentation trilemma: high segmentation performance, preserved dialogue ability, and fast inference. Embedding-prediction methods may disrupt language modeling through pixel-level objectives, whereas next-token generation is… 36 r/LocalLLaMA community 25d ago I updated my localy run benchmark with DeepSeek V4 Flash 0731 It's the purple cluster on the top left (the good corner...) I'm running the MXFP4 version from Bartoswski with Dspark at 1K t/s prefill and 90 t/s gen (average). I tried different sampling params, you can check the detail. It's very efficient while scoring the best yet. Too bad… 12 Hugging Face Daily Papers research 25d ago When Agents Learn to Be You: Benchmarking Privacy Leakage, Impersonation Risk, and Defenses in Persona Skills Abstract Persona skills distill personal interaction histories into portable and executable artifacts for downstream agents. While enabling flexible personalization, this process concentrates fragmented personal signals, amplifies their impact through reuse, and challenges… 29 arXiv — Machine Learning research 25d ago Multimodal Auto-regressive Transformer Surrogate for Modeling Variable Operations and Quantifying Uncertainty in Geological Carbon Storage arXiv:2608.02629v1 Announce Type: new Abstract: The use of variable well perforation and injection strategies can improve the efficiency of geological carbon storage operations. We develop a new multimodal auto-regressive transformer surrogate to model these operations under… 24 arXiv — Machine Learning research 25d ago GoT-CD: Graph-of-Thoughts Causal Discovery and the Fragility of Post-hoc Path-Specific Fairness Audits arXiv:2608.02877v1 Announce Type: new Abstract: Causal discovery recovers directed structure from observational data and is increasingly used in clinical settings to support mechanism reasoning and fairness audits of predictive models. Path-specific counterfactual fairness asks… 8 Page 7 of 10 · 500 articles ← Newer Older →
