News / #rag Tag Rag 500 articles archived under #rag · RSS Sign in to follow arXiv — NLP / Computation & Language research 5d ago Measuring Cultural Alignment Beyond the Average: A Framework for Evaluating Maternal-Health LLM Interactions in Indian Contexts arXiv:2610.11586v1 Announce Type: new Abstract: Existing evaluation methods for healthcare LLMs primarily assess factual correctness,safety, and fluency, while providing limited insight into whether generated interactions reflect culturally situated healthcare reasoning. This… 23 arXiv — NLP / Computation & Language research 5d ago Forms of LLM-Integrated Applications from LLM-Chats to Autonomous AI Agent System arXiv:2610.11899v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly embedded as components in software systems, marketed under labels such as chatbot, copilot, retrieval-augmented generation, workflow, coding agent and AI agent. Whether these labels… 36 arXiv — NLP / Computation & Language research 5d ago A persistent accuracy ceiling in automated verbal deception detection arXiv:2610.12118v1 Announce Type: new Abstract: Automated methods have been proposed to overcome the limitations of human verbal deception detection, but evidence remains fragmented across disciplines. We systematically reviewed 25 years of research (289 reports, 6,136… 13 arXiv — NLP / Computation & Language research 5d ago GameCommBench: A Unified Benchmark and Type-Aware Evaluation for AI-Generated Game Commentary arXiv:2610.11129v1 Announce Type: cross Abstract: Game commentary is an open-ended generation task requiring multimodal perception, strategic reasoning, and contextual knowledge. Existing AI-Generated Game Commentary (AI-GGC) studies remain fragmented across games, modalities,… 29 r/MachineLearning community 6d ago Production Grade Retrieval Pipeline That Admits "I Don't Know" [P] If you're moving a RAG prototype to production, this is the checklist I wish I'd had. - Citations on every answer - Refusing when the context doesn't support one - Access control that can't be bypassed - Ingestion that never blocks a user Enjoy !! https://youtu.be/-GK1e4KZqhw… 10 llama.cpp releases dev-tools 6d ago b11512 model : fix DFlash output head sharing ( #30111 ) llama : fix DFlash output head sharing Assisted-by: Codex dflash : read tied output weights from GGUF metadata Assisted-by: Codex llama : share tied word embedding metadata Assisted-by: Codex llama : remove DFlash embedding head… 23 arXiv — Machine Learning research 6d ago A Self-Pruning Transformer: Extreme KV-Cache Compression with Universal Attention arXiv:2610.09051v1 Announce Type: new Abstract: The large KV-cache size of modern LLMs creates a barrier to efficient deployment. Recent work has explored replacing attention layers' RoPE positional embeddings with alternative decay-based mechanisms, which can then be used to… 30 arXiv — Machine Learning research 6d ago Breaking Adversarial Transferability in Fine-Tuned Speech Recognition arXiv:2610.09109v1 Announce Type: new Abstract: Many organizations fine-tune publicly available pretrained Automatic Speech Recognition (ASR) models and deploy them in black-box settings, assuming limited access provides protection. We show this assumption is fragile:… 31 arXiv — Machine Learning research 6d ago The Deceptive Bandit Problem: Exploratory Coupling and the Fragility of Multi-Agent Learning arXiv:2610.09120v1 Announce Type: new Abstract: Randomized exploration is central to bandit learning, multi-agent reinforcement learning, and zeroth-order policy search, yet its independence and privacy are usually only treated as technical assumptions. We show that these… 11 arXiv — Machine Learning research 6d ago Q-PACE: Dynamic Precision Allocation for Quantization-Aware Training arXiv:2610.09183v1 Announce Type: new Abstract: Quantization-aware training (QAT) leverages lower-precision arithmetic to reduce the cost of LLM deployment, but aggressive quantization degrades final model performance. A common remedy is mixed-precision training, in which high… 22 arXiv — Machine Learning research 6d ago Patient, Place, Prior (P$^3$): What Counts as Personalization in Medical World Models? arXiv:2610.09194v1 Announce Type: new Abstract: Longitudinal models forecast how a patient's imaging state evolves, but accuracy does not show whether the patient's observed trajectory drives the prediction. A population-average forecast may be useful but cannot establish a… 36 arXiv — Machine Learning research 6d ago Exact Dynamics and Finite-Sample Trajectory Recovery of Linear Recursive Feature Machines arXiv:2610.09196v1 Announce Type: new Abstract: Recursive feature machines (RFMs) learn representations of data by alternating between fitting a predictor to a dataset and updating features of that predictor using the average gradient outer product (AGOP). Connections between… 7 arXiv — Machine Learning research 6d ago Shared Low-rank Basis Factorization for Data-free Mixture-of-Experts Compression arXiv:2610.09342v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) large language models decouple capacity from compute through sparse routing, but their large parameter count creates storage and serving challenges. We analyze three MoE compression families: expert… 28 arXiv — Machine Learning research 6d ago GeoPrior-Mamba: Structured Process Priors with Mamba for Fine-Resolution XCO2 Reconstruction arXiv:2610.09456v1 Announce Type: new Abstract: Reconstructing fine-resolution column-averaged dry-air CO2 (XCO2) fields from sparse satellite observations requires models to infer spatial structure that is only weakly constrained by direct measurements. Existing learning-based… 25 arXiv — Machine Learning research 6d ago Safe on Average, Unsafe in the Tail: When Is the Episodic-Cost Tail Controllable? arXiv:2610.09508v1 Announce Type: new Abstract: Safe reinforcement learning seeks policies that maximize return while satisfying constraints on cumulative cost. Most methods impose these constraints on expected episodic cost. Consequently, standard evaluations report mean… 15 arXiv — Machine Learning research 6d ago Lightweight and Versatile Learned Optimization by Recombination of Gradient History arXiv:2610.09604v1 Announce Type: new Abstract: This paper presents a lightweight and versatile learned optimizer that dynamically recombines gradient history, represented as averages over disjoint time spans. The optimizer reduces the prediction space to one scalar coefficient… 26 arXiv — NLP / Computation & Language research 6d ago Leveraging LLM-Generated Explanations for Detecting Emotionally Rewritten Fake News arXiv:2610.08835v1 Announce Type: new Abstract: The spread of fake news may cause severe social consequences. Existing fake news detection methods mainly focus on stylistic variations or incorporate external information such as explanations. However, news articles are often… 32 arXiv — NLP / Computation & Language research 6d ago ToolRACER: A Robust Agentic Conversation Emulation Resource for Agent Training and Evaluation arXiv:2610.09163v1 Announce Type: new Abstract: Task-oriented conversational agents remain fragile under real world conversation scenarios as they rarely follow a predictable script, especially when users exhibit non-cooperative behavior. Existing function-calling benchmarks… 12 arXiv — NLP / Computation & Language research 6d ago A Deafening Silence: Catastrophic Forgetting Lives in the Output Embeddings of Tokens the Data Never Speaks arXiv:2610.09835v1 Announce Type: new Abstract: Continual pre-training and fine-tuning in Large Language Models (LLMs) inevitably induce catastrophic forgetting, typically mitigated by replay using often-inaccessible original data. In this data-free regime, we analyze where… 35 arXiv — NLP / Computation & Language research 6d ago Cache the Encoder Within:Compact, Reusable Memory across LLM Queries arXiv:2610.10058v1 Announce Type: new Abstract: Repeated queries over shared documents incur redundant encoding, while caching model states introduces persistent storage costs. Building on CoMem's intermediate-state interface, EncBank treats a pretrained LLM's lower layers as a… 15 arXiv — NLP / Computation & Language research 6d ago HySPE: Positional Encoding via Symplectic Dual Shears arXiv:2610.10154v1 Announce Type: new Abstract: We introduce Hyperbolic Symplectic Positional Encoding (HySPE), grounding positional attention in non-compact symplectic transformations. While canonical Rotary Position Embedding (RoPE) parameterizes the compact, elliptic branch… 35 arXiv — NLP / Computation & Language research 6d ago Document-Level Text Simplification in Estonian Using Large Language Models arXiv:2610.10378v1 Announce Type: new Abstract: Document-level text simplification involves transformations that go beyond sentence-internal edits, addressing discourse coherence, anaphora resolution, and cross-paragraph consistency. Despite advances in sentence-level… 12 arXiv — NLP / Computation & Language research 6d ago Your Prompt Should Do More: Effects of Retrieval Instructions in Embedding Models arXiv:2610.10508v1 Announce Type: new Abstract: Prompted embedding models have recently received increasing attention, particularly for retrieval, where detailed retrieval instructions are provided as part of the retrieval prompt. Several new datasets and studies have examined… 32 arXiv — NLP / Computation & Language research 6d ago EngramEdit: Decoupled Knowledge Updates in LLMs through Conditional Memory arXiv:2610.10533v1 Announce Type: new Abstract: Conditional memory architectures such as DeepSeek Engram use input n-grams to look up learned embeddings, expanding the capacity of large language models (LLMs) with limited additional computation. Beyond model scaling, this… 29 arXiv — NLP / Computation & Language research 6d ago How Fragile Is On-Device Language Model Safety? Localizing Safety-Critical Parameters for Sparse Fault Analysis arXiv:2610.09000v1 Announce Type: cross Abstract: As small language models (SLMs) are increasingly deployed on resource-constrained and on-device platforms, including as components of agentic systems, the integrity of locally stored model parameters becomes an important safety… 19 arXiv — NLP / Computation & Language research 6d ago BEACON-SP: Ontology-Grounded GraphRAG Framework for Clinical Suicide Risk Assessment arXiv:2610.09026v1 Announce Type: cross Abstract: We present BEACON-SP, an ontology-grounded Graph Retrieval-Augmented Generation (GraphRAG) framework for clinician-facing decision support in behavioral health settings such as suicide prevention, where effective assessment… 18 arXiv — NLP / Computation & Language research 6d ago TopoGraphRAG-Bench: Evaluating Multimodal GraphRAG on Layout-Grounded Evidence Reasoning arXiv:2610.09360v1 Announce Type: cross Abstract: Real-world documents distribute evidence across text, tables, figures, and captions within complex page layouts. Answering complex questions over such documents therefore requires more than retrieving relevant passages: systems… 33 arXiv — NLP / Computation & Language research 6d ago Finding the Right Balance: Relevance and Diversity in LLM Retrieval arXiv:2610.09412v1 Announce Type: cross Abstract: Retrieval diversification is widely available in retrieval-augmented generation (RAG) frameworks, yet prior studies disagree on whether it improves retrieval and answer quality. We show that its effectiveness varies primarily… 37 TechCrunch — AI news-outlet 7d ago ChatGPT for Teens keeps teens talking, even during mental health crises ChatGPT’s teen safeguards are meant to protect vulnerable users, but new testing found the chatbot continues encouraging engagement during crises and potentially encourages unhealthy relationships with the AI itself. 10 r/LocalLLaMA community 7d ago Image-text retrieval with EmbeddingGemma 2's vision tower, running in the browser on WebGPU EmbeddingGemma 2 came out this week. It maps images and text into one 768-dim space, so you can search photos by describing them. I ported its text and vision towers to ruNNtime, a WebGPU inference library in TypeScript, and made a small photo gallery where search runs entirely… 28 r/LocalLLaMA community 7d ago Local RAG for a personal second brain: embedder and hybrid retrieval picks in 2026? Building a fully local RAG setup for personal notes (life-logging second brain, single user, privacy is the whole point so no hosted APIs for the data). Stack is SQLite + sqlite-vec + FTS5, Ollama for embeddings and generation, all on an Apple Silicon Mac. Two questions where… 23 arXiv — Machine Learning research 7d ago TEMPEST: Temporal Embeddings for Scalable Driver Identification via Angular Margin Learning arXiv:2610.06855v1 Announce Type: new Abstract: Scalable driver identification requires embedding models that maintain discriminative performance as fleet size grows, yet existing triplet-loss formulations degrade rapidly with driver pool size and overfit to session-specific… 35 arXiv — Machine Learning research 7d ago Uncertainty in Representation Learning on Knowledge Graphs arXiv:2610.06974v1 Announce Type: new Abstract: Knowledge graph embedding (KGE) methods represent entities and predicates in continuous vector spaces to infer missing knowledge. Despite strong benchmark performance, their predictions often lack principled reliability guarantees,… 9 arXiv — Machine Learning research 7d ago DART-ES: Difficulty-Aware Reweighting and Targeted Replay for Fine-Tuning LLMs with Evolution Strategies arXiv:2610.06993v1 Announce Type: new Abstract: Evolution Strategies (ES) enable memory efficient full parameter fine-tuning of large language models (LLMs) using only forward computation. However, standard ES uniformly averages rewards across problems and compresses problem… 16 arXiv — Machine Learning research 7d ago CausalBind: Causal Modeling and Learning for Protein-Molecule Virtual Screening arXiv:2610.07340v1 Announce Type: new Abstract: Protein-molecule virtual screening is increasingly cast as a problem of representation learning in a shared embedding space. Existing methods rely on dense holistic alignment, entangling invariant binding determinants with nuisance… 12 arXiv — Machine Learning research 7d ago AlignQuant: Tile-Aligned Mixed-Precision Quantization for Efficient LLM Generation arXiv:2610.07457v1 Announce Type: new Abstract: Fine-grained mixed-precision quantization promises efficient large language model inference, but local precision choices can conflict with regular GPU storage and computation units. This precision-boundary mismatch limits the… 4 arXiv — Machine Learning research 7d ago Harmful SFT Leaves a Continuous Trace in LLM Checkpoint Updates arXiv:2610.07518v1 Announce Type: new Abstract: Safety auditing of post-trained large language models typically relies on model behavior, requiring model execution and depending on the coverage of available evaluations. This work asks a different question: Do the target… 32 arXiv — NLP / Computation & Language research 7d ago Tree Navigation Without LLM Summaries: A Matched-Cost Study of Hierarchical Retrieval for Long-Document QA arXiv:2610.06902v1 Announce Type: new Abstract: Retrieval-augmented generation grounds language models in external context, but for long documents flat top-$k$ retrieval can cluster on a single region and miss complementary evidence. RAPTOR-style summary trees address this by… 36 arXiv — NLP / Computation & Language research 7d ago WavePrune: One period is often enough for RoPE arXiv:2610.06963v1 Announce Type: new Abstract: Rotary Position Embedding (RoPE) encodes token positions by rotating each two-dimensional channel of the query and key vectors at a channel-specific frequency, making the attention logits invariant to a common shift of positions.… 36 arXiv — NLP / Computation & Language research 7d ago Two Vectors Replace In-Context Demos: Structured Task Adaptation via Embeddings arXiv:2610.07572v1 Announce Type: new Abstract: In-context learning (ICL) adapts frozen large multimodal models (LMMs) to new tasks from a few demonstrations (demos), but re-encodes them at every query, where each demo image adds up to hundreds of visual tokens. Demo-free… 14 arXiv — NLP / Computation & Language research 7d ago Reading, Not Manipulating: Leveraging Router Logits for Multimodal Safety in MoE Vision-Language Models arXiv:2610.07774v1 Announce Type: new Abstract: Vision-language models (VLMs) face compositional safety risks where harmful intent emerges from the interaction between visual and textual inputs. As mixture-of-experts (MoE) VLMs become increasingly common, recent work has… 9 arXiv — NLP / Computation & Language research 7d ago Leveraging a four-quadrant approach for evaluating Redpine Science arXiv:2610.07937v1 Announce Type: new Abstract: Redpine Science gives models and agents a single access point to a wide range of peer-reviewed literature, queried directly through the Model Context Protocol (MCP) and an API. This report evaluates Redpine Science on two levels:… 27 arXiv — NLP / Computation & Language research 7d ago Rethinking Cross-Tokenizer On-Policy Distillation: From Alignment Coverage to Supervision Reliability arXiv:2610.08448v1 Announce Type: new Abstract: On-Policy Distillation (OPD) trains a student on its own generations using teacher feedback. With different tokenizers, comparing teacher and student predictions requires alignment at both sequence and vocabulary levels. In this… 26 arXiv — NLP / Computation & Language research 7d ago Agentic AutoRAG: RAG Pipeline Optimization through Reasoning-Driven Agents arXiv:2610.08452v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) is a widely used approach for grounding large language models (LLMs) in external knowledge. However, configuring a pipeline is an expensive hyperparameter optimization problem over many… 21 arXiv — NLP / Computation & Language research 7d ago UNREAL: Unifying Retrieval and Long-Context with a Single Model arXiv:2610.08463v1 Announce Type: new Abstract: Long-context inference and Retrieval-Augmented Generation (RAG) handle evidence selection at vastly different scales, from a single long prompt to an entire corpus. We ask whether a single model-internal mechanism can select… 19 arXiv — NLP / Computation & Language research 7d ago Generative AI translations in high-stakes emergency messaging arXiv:2610.08601v1 Announce Type: new Abstract: Emergency messaging such as extreme-weather reports and earthquake instructions can involve high stakes, to the extent that translation errors can lead to tragic consequences. The use of machine translation or generative artificial… 27 arXiv — NLP / Computation & Language research 7d ago AegisFlow: A Multi-Agent Agentic AI Framework for Autonomous Remediation and Self-Healing in Fragile Data Ecosystems arXiv:2610.06971v1 Announce Type: cross Abstract: Traditional data pipelines are notoriously brittle, often failing due to upstream schema drift, API contract changes, or website DOM modifications. Present observability tools only raise alerts but for human engineers, resulting… 23 arXiv — NLP / Computation & Language research 7d ago Jailbreaking Open-Weight LLMs via Random Embedding Perturbations arXiv:2610.07125v1 Announce Type: cross Abstract: While open-weight models have enjoyed steady progress in capabilities and wide adoption across multiple domains, their safety remains an important concern. One key feature is the ability to refuse or deflect harmful, malicious,… 38 Simon Willison community 8d ago EmbeddingGemma 2 My comment on EmbeddingGemma 2 — Hacker News. I really appreciate that EmbeddingGemma 2 is under the Apache 2.0 license. For embedding models in particular, I don't think it makes sense to use a closed, proprietary, hosted-only model. Most applications of embedding models… 37 Google DeepMind official-blog 8d ago EmbeddingGemma 2: an open, lightweight multimodal embedding model EmbeddingGemma 2: an open, lightweight multimodal embedding model Oct 06, 2026 | x.com Facebook LinkedIn Mail EmbeddingGemma 2 is the most capable model for on-device multimodal embeddings, natively mapping combinations of text, images, audio, and video into a unified embedding… 4 Page 2 of 10 · 500 articles ← Newer Older →
