News / #rag Tag Rag 500 articles archived under #rag · RSS Sign in to follow arXiv — NLP / Computation & Language research 17d ago Mwando: Leveraging AI to Preserve and Teach shiKomori arXiv:2607.23481v1 Announce Type: new Abstract: This paper presents Mwando, a virtual educational assistant designed to support the teaching and preservation of shiKomori, the language of the Comoros Islands. The system covers the four main dialectal variants (shiNgazidja,… 7 arXiv — NLP / Computation & Language research 17d ago The JEPA Paradox in Language: The Geometry of Linguistic Alternatives arXiv:2607.23531v1 Announce Type: new Abstract: Joint-Embedding Predictive Architectures (JEPAs) are effective for images, video, and audio, yet deterministic JEPA-style latent prediction has not become a standard objective for text encoders. We argue that this gap reflects a… 37 arXiv — NLP / Computation & Language research 17d ago An empirical investigation into the properties of standard word embeddings arXiv:2607.23675v1 Announce Type: new Abstract: The embedding of word sequences into continuous vector spaces has been one of the most important developments in Natural Language Processing in the recent past. Such embeddings have found application in areas such as Automatic… 21 arXiv — NLP / Computation & Language research 17d ago Cross-Attention Calibrated Deduplication for Retrieval-Augmented Generation System arXiv:2607.24332v1 Announce Type: new Abstract: Common chunking strategies in Retrieval-Augmented Generation (RAG) systems often create redundant chunks. These redundant chunks make the vector database bigger and slow down retrieval. A common fix is cosine-similarity… 13 arXiv — NLP / Computation & Language research 17d ago Retrieval-Augmented Large Language Models as Components of Cognitive Computing architecture for Regulatory Knowledge Management arXiv:2607.24352v1 Announce Type: new Abstract: The aim of this article is to verify whether integrating large language models (LLMs) with the Retrieval-Augmented Generation (RAG) architecture enables their transformation from standalone generative models into components of… 18 arXiv — NLP / Computation & Language research 17d ago Source-Aware Reranking for Retrieval-Augmented Generation: A Reliability Prior Approach arXiv:2607.22584v1 Announce Type: cross Abstract: Standard Retrieval-Augmented Generation pipelines rank retrieved documents by semantic similarity alone, without accounting for source provenance or credibility. This work evaluates a simple and interpretable modification to RAG… 5 arXiv — NLP / Computation & Language research 17d ago Structure Over Scale: Schema-Constrained Causal Graphs for RAG arXiv:2607.22592v1 Announce Type: cross Abstract: Graph-based retrieval-augmented generation (GraphRAG) grounds answers in structured knowledge, but current systems extract entities and relationships exhaustively, producing graphs whose size and construction cost scale with… 17 arXiv — NLP / Computation & Language research 17d ago Revitalizing Public Urban Places through Cultural and Political Memory: A Technological Approach with LLMs and Augmented Reality arXiv:2607.22613v1 Announce Type: cross Abstract: This paper explores the intersection of memory, place, and identity, examining how new technologies, particularly Apple Vision Pro, can illuminate this nexus. Leveraging digital twins and virtual reality, it investigates how… 23 Hugging Face Daily Papers research 17d ago Leveraging External Knowledge for Historical Document Restoration via Retrieval-Augmented Large Language Models Abstract Historical documents act as invaluable knowledge archives but often suffer from illegibility due to physical deterioration and damage. While existing restoration methods based on masked language modeling effectively utilize local context, they struggle to restore named… 37 r/LocalLLaMA community 17d ago Why Anthropic's battle is meant to poison the wells of open weight models, in 3 steps. It doesn't solve any problems. Just a few paragraphs above, he says he fears that authoritarian states (he names China, and possibly others) can use their models to do evil stuff. And surely enough, malicious actors creating a model for themselves and for the EVILZ aren't going… 24 arXiv — Machine Learning research 18d ago Toward Goal-Agnostic Joint-Embedding Predictive Control of Partial Differential Equations arXiv:2607.21644v1 Announce Type: new Abstract: We present a goal-agnostic control framework for partial differential equations (PDEs) built around a joint-embedding predictive architecture (JEPA). The small 2D ViT encoder and action-conditioned latent dynamics are trained… 36 arXiv — Machine Learning research 18d ago Encoding Invisible Causation for Bridge Diagnostic Agents: Triple-Guided Retrieval-Augmented Fine-Tuning with QLoRA arXiv:2607.21680v1 Announce Type: new Abstract: Bridge infrastructure deteriorates gradually, yet its root causes---salt intrusion, freezing, fatigue cracking, and others---remain invisible to the naked eye. Expert diagnosis relies on tacit knowledge built over years of… 21 arXiv — Machine Learning research 18d ago Unbiased Open World Regularization for Fair Self-Supervised Learning arXiv:2607.22149v1 Announce Type: new Abstract: Despite recent advances, self-supervised learning (SSL) models and Joint-Embedding Predictive Architectures (JEPAs) remain susceptible to learning spurious biases in the dataset. These techniques rely on regularization, which… 19 arXiv — Machine Learning research 18d ago IQ-JEPA: A Joint-Embedding Predictive Architecture with a Hermitian Vision Transformer for Sound Speed and Attenuation Estimation from Ultrasound IQ Data arXiv:2607.22351v1 Announce Type: new Abstract: The speed of sound in tissue is a prerequisite for well-focused imaging and has diagnostic value, but recovering it from raw pulse-echo channel data is fundamentally a nonlinear inverse problem. Learned solvers are fast yet label… 25 arXiv — Machine Learning research 18d ago On the Identifiability of Controlled World Models arXiv:2607.22430v1 Announce Type: new Abstract: Learning world models that infer environment dynamics from high-dimensional observations and predict outcomes under candidate actions is central to planning and control. Joint-Embedding Predictive Architectures (JEPAs) provide a… 8 arXiv — Machine Learning research 18d ago Phylogenetic signal in marine mammal and bird vocalizations captured by audio foundation models: the limited benefit of domain-specific pretraining arXiv:2607.22458v1 Announce Type: new Abstract: Do learned audio embeddings encode structure that nobody told them to encode? We probe four large pretrained audio models (AST, CLAP, BEATs-bio and BirdNET) with a downstream task none of them saw during training: recovering… 17 arXiv — NLP / Computation & Language research 18d ago Leveraging External Knowledge for Historical Document Restoration via Retrieval-Augmented Large Language Models arXiv:2607.21936v1 Announce Type: new Abstract: Historical documents act as invaluable knowledge archives but often suffer from illegibility due to physical deterioration and damage. While existing restoration methods based on masked language modeling effectively utilize local… 27 arXiv — NLP / Computation & Language research 18d ago MEUSLI: a Multilingual Projector for LLM-based ASR and Beyond arXiv:2607.22100v1 Announce Type: new Abstract: Lightweight projectors are an established way to connect pre-trained speech encoders with large language models (LLMs), mapping acoustic features into token-level embeddings for tasks like ASR and spoken question answering.… 24 arXiv — NLP / Computation & Language research 18d ago From Isolated Tasks to Structured Capabilities: A Multilayer Taxonomy for Large Language Models arXiv:2607.22182v1 Announce Type: new Abstract: Large language model (LLM) evaluation spans diverse tasks and benchmarks, yet evidence remains organized around tasks rather than the capabilities they probe. This fragmentation limits cross-study comparison, obscures capabilities… 30 arXiv — NLP / Computation & Language research 18d ago Nanbeige4.2-3B: Unlocking Agentic Capabilities in a Compact Mode arXiv:2607.22083v1 Announce Type: cross Abstract: We present Nanbeige4.2-3B, a compact general agentic model with 3B non-embedding parameters. It delivers strong performance across code-agent, office-agent, and complex tool-use tasks while maintaining highly competitive… 12 arXiv — NLP / Computation & Language research 18d ago Interpretable Depression Detection from Social Media Text Using LLM-Derived Embeddings arXiv:2506.06616v2 Announce Type: replace Abstract: Accurate and interpretable detection of depressive language in social media can support early identification of mental health conditions and inform timely interventions. In this paper, we investigate the use of large language… 13 arXiv — NLP / Computation & Language research 18d ago LMEB: Long-horizon Memory Embedding Benchmark arXiv:2603.12572v5 Announce Type: replace Abstract: Memory embeddings are crucial for memory-augmented systems, such as OpenClaw, but their evaluation is underexplored in current text embedding benchmarks, which narrowly focus on traditional passage retrieval and fail to assess… 27 arXiv — NLP / Computation & Language research 18d ago SURE-RAG: Sufficiency and Uncertainty-Aware Evidence Verification for Selective Retrieval-Augmented Generation arXiv:2605.03534v2 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) grounds answers in retrieved passages, yet relevance does not guarantee sufficiency: a topical passage may still fail to justify the answer. We study evidence sufficiency verification for… 14 r/LocalLLaMA community 19d ago ai-sage/GigaChat3.1-Audio-10B-A1.8B · Hugging Face GigaChat Audio 10B is an audio-native LLM built on top of the GigaChat 3.1 Lightning text model. A Conformer speech encoder and a modality adapter feed audio embeddings directly into a Mixture-of-Experts decoder, so the model keeps the text quality of its base while adding… 36 Hugging Face Daily Papers research 19d ago VisCo: Leveraging Large Language Models as Intrinsic Encoders for Visual Token Compression Abstract Vision-language models (VLMs) process large numbers of visual tokens, resulting in substantial inference latency and memory overhead. This has motivated extensive research on visual token compression. While training-free strategies rely on heuristic metrics and suffer… 12 arXiv — Machine Learning research 21d ago Multimodal CoLRAG-TF: Triple-Filtered Retrieval for Complex PDFs arXiv:2607.20517v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) over heterogeneous PDF collections remains challenging due to multimodal content, domain-specific terminology, and the need for multi-hop reasoning across dispersed evidence. We present… 14 arXiv — Machine Learning research 21d ago Leveraging Biokinetic Knowledge Priors for Data-Scarce Bioprocess Modeling arXiv:2607.20539v1 Announce Type: new Abstract: While deep learning has accelerated drug discovery, its impact on biomanufacturing has been considerably more limited. The reason is data scarcity. Bioreactor experiments are high-cost, take days to weeks, and are rarely shared in… 17 arXiv — Machine Learning research 21d ago SenCos-GEM: SENet-Calibrated and Law-of-Cosines-Constrained Geometry-Enhanced Molecular Representation for Property Prediction arXiv:2607.20551v1 Announce Type: new Abstract: Effective molecular representation learning is crucial for accurate molecular property prediction. Recently, numerous self-supervised learning (SSL) approaches leveraging 3D GNNs have been developed to capture comprehensive 3D… 5 arXiv — Machine Learning research 21d ago Joint Utilization of Geospatial and census proxies for Autoencoder-Assisted Downscaling (JUGAAD) of socioeconomic indicators in India arXiv:2607.20559v1 Announce Type: new Abstract: Monitoring poverty and food security indicators is imperative for addressing socioeconomic challenges in developing nations. A limitation is mismatches in scale between data sources: census data provide geographic coverage, while… 29 arXiv — Machine Learning research 21d ago Chronofy: A Temporal-Logical Decay Architecture for Information Validity in Time-Aware Retrieval-Augmented Generation arXiv:2607.20560v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) systems retrieve and integrate external knowledge to ground large language model (LLM) outputs. However, current RAG architectures treat all retrieved facts as equally valid regardless of… 7 arXiv — Machine Learning research 21d ago CT-Merging: Consensus Directions and Task-Level Scaling for LoRA Adapter Merging arXiv:2607.20561v1 Announce Type: new Abstract: LoRA adapters provide an efficient way to specialize a pretrained model for many downstream tasks, but deploying one adapter per task requires adapter storage and task selection at inference time. Model merging addresses this issue… 29 arXiv — Machine Learning research 21d ago End-to-End Learning of Safe Optimal Feedback Control in High Dimensions with Control Barrier Function Layers arXiv:2607.20674v1 Announce Type: new Abstract: We consider the problem of learning high-dimensional semi-global feedback controllers under hard safety constraints enforced by control barrier functions (CBFs). Incorporating CBFs into end-to-end policy training requires embedding… 5 arXiv — NLP / Computation & Language research 21d ago GaugeQuant: Online Learning of Quantization-Optimal Bases from LLM Symmetries arXiv:2607.20757v1 Announce Type: cross Abstract: Transformers are known to have internal continuous symmetries that leave outputs invariant, while modifying quantization. GaugeQuant leverages this in-training by introducing a LogSumExp term to the loss that breaks the… 24 arXiv — Machine Learning research 21d ago External Clustering Validation by the Homogeneity-Parsimony Trade-off arXiv:2607.20799v1 Announce Type: new Abstract: Scalar metrics are often used to evaluate clusterings against known classes, but they can obscure a fundamental trade-off: clusterings should be informative about class labels while avoiding unnecessary fragmentation. Here we… 34 arXiv — Machine Learning research 21d ago Three-Pronged Spectral Control for Federated Parameter Efficient Fine Tuning arXiv:2607.20914v1 Announce Type: new Abstract: Federated parameter-efficient fine-tuning (PEFT) enables communication-efficient adaptation of large pretrained models on decentralized edge data, but it remains fragile under non-IID client heterogeneity. In low-rank adaptation… 4 arXiv — Machine Learning research 21d ago ADABORD: a novel AdaBoost approach for ordinal classification arXiv:2607.21003v1 Announce Type: new Abstract: Ordinal Classification (OC) deals with classification tasks where the classes follow a natural order. Despite the progress in OC, many existing approaches fail to fully leverage the ordinal information, treating the problem as… 32 arXiv — Machine Learning research 21d ago Spectral Transformation for Layer-wise Global Rank Discovery in Federated LoRA for Vision Transformers arXiv:2607.21074v1 Announce Type: new Abstract: Fine-tuning Vision Transformers (ViTs) with low-rank adapters (LoRA) promises better communication efficiency under federated setup, yet existing aggregation strategies face fundamental limitations. Independently averaging these… 28 arXiv — Machine Learning research 21d ago Filter Learning for Subgraphs: Algebras and Performance Risk Bounds arXiv:2607.21263v1 Announce Type: new Abstract: Graph signal processing tasks that leverage spectral information typically assume access to the complete graph topology, which is often unavailable in practice. We propose a systematic framework for subgraph filter learning (SFL),… 38 arXiv — Machine Learning research 21d ago Semantic-Aware Task Clustering for Constructive and Cooperative Multi-Tasking arXiv:2607.21426v1 Announce Type: new Abstract: Cooperative multi-task semantic communication (CMT-SemCom) improves task execution performance by leveraging shared representations. However, as we demonstrated in [1], cooperative multi-tasking can be either constructive or… 16 arXiv — NLP / Computation & Language research 21d ago Human-in-the-Loop Large Language Model Framework for Identification of Cutaneous Immune-Related Adverse Events arXiv:2607.20428v1 Announce Type: new Abstract: This study evaluated a retrieval-augmented, multi-agent large language model (LLM)-driven, human-in-the-loop framework for detecting cutaneous immune-related adverse events (cirAEs) from clinical notes. Compared with unassisted… 28 arXiv — NLP / Computation & Language research 21d ago LLM-INSTRUCT at UZH Shared Task 2026: Constraint-Aware Retrieval and Selective Debate for Paragraph-Level Argument Mining arXiv:2607.20430v1 Announce Type: new Abstract: We present LLM-INSTRUCT, the winning system for the UZH Shared Task at ArgMining 2026 on paragraph-level argument mining in UN and UNESCO resolutions. The task requires paragraph-type classification, prediction of a subset of 141… 30 arXiv — NLP / Computation & Language research 21d ago Skill-Contracted Agents for Evidence-Aware Materials Literature Analysis arXiv:2607.20431v1 Announce Type: new Abstract: Materials science literature analysis requires simultaneous attention to composition, processing, characterization, and property relationships, yet conventional retrieval-augmented generation pipelines struggle to reconcile… 36 arXiv — NLP / Computation & Language research 21d ago Making Open-Source Text LLM Watermarks Durable Against Merging arXiv:2607.20435v1 Announce Type: new Abstract: Open-source LLMs (OSMs)arereaching near state-of-the-art performance, prompting prior works to trace the text they generate by embedding text watermarking algorithms directly into their weights. Yet, OSMs are subject to… 5 arXiv — NLP / Computation & Language research 21d ago TopoGuard: Graph Theory Based Defenses Against Split-Knowledge Attacks on RAG arXiv:2607.20437v1 Announce Type: new Abstract: Production Retrieval Augmented Generation (RAG) systems rely on aggregating multiple external documents to answer complex queries. However, the retrieved documents introduce a new threat surface that can be exploited to launch… 24 arXiv — NLP / Computation & Language research 21d ago PrefReward: Learning User Preference Matrix for Personalized Text Generation arXiv:2607.21067v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable ability in generating personalized content by leveraging user histories and contextual cues. However, most existing personalization approaches rely on implicit… 33 arXiv — NLP / Computation & Language research 21d ago Progressive Cramming: Reliable Token Compression and What It Reveals arXiv:2607.21231v1 Announce Type: new Abstract: Token cramming compresses sequences into learned embeddings with near-perfect reconstruction, but fixed token budgets and 99\% accuracy thresholds leave it unclear whether residual errors reflect optimization failures or… 14 arXiv — NLP / Computation & Language research 21d ago A Comparative Evaluation of Embeddings and LLMs in a Greek Book Publisher Setting - The CUP Dataset arXiv:2607.21274v1 Announce Type: new Abstract: We present CUP, a Greek book retrieval benchmark consisting of 868 catalog records and 104 expert-annotated queries with graded relevance judgments. We evaluate sparse (BM25), dense (sentence-transformers), hybrid, and LLM-assisted… 20 arXiv — NLP / Computation & Language research 21d ago GRADRAG: Cross-Component Prompt Adaptation for Coordinated Multi-Agent RAG arXiv:2607.21324v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) systems increasingly employ multiple LLM agents. Yet, most prior work optimizes components in isolation rather than coordinating improvements across the pipeline. We introduce GRADRAG, a… 32 arXiv — NLP / Computation & Language research 21d ago Word meaning co-determines vowel-inherent spectral change. A corpus-based investigation of conversational Mandarin arXiv:2607.21391v1 Announce Type: new Abstract: This study investigates vowel-inherent spectral change (VISC) in spontaneous conversational Mandarin. Using the generalized additive model and word embeddings from distributional semantics, we show that, when controlling for… 34 arXiv — NLP / Computation & Language research 21d ago MemTools: A Unified Research Framework for Interoperable Agent Memory arXiv:2607.21404v1 Announce Type: new Abstract: While memory systems are essential for agent architectures, pervasive architectural fragmentation restricts systematic research. Existing implementations typically couple different stages of the memory lifecycle, entangle… 35 Page 6 of 10 · 500 articles ← Newer Older →
