Retrieval-augmented generation

Retrieval pipelines, vector search, chunking and reranking: how models are grounded in a corpus instead of their weights.

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arXiv AI

Jul 23

NeuroSymActive: Differentiable Neural-Symbolic Reasoning with Active Exploration for Knowledge Graph Question Answering

arXiv:2602. 15353v3 Announce Type: replace-cross Abstract: Large pretrained language models and neural reasoning systems have advanced many natural language tasks, yet they remain challenged by knowledge-intensive queries that require precise, structured multi-hop inference.

By Rong Fu, Yang Li, Zeyu Zhang, Jiekai Wu, Yaohua Liu, Shuaishuai Cao, Yangchen Zeng, Yuhang Zhang, Xiaojing Du, Simon Fong

llms rag nlp benchmarks

arXiv AI

Jul 23

GraphContainer: A Unified Platform for Comparing and Debugging Graph RAG Methods

arXiv:2607. 19362v1 Announce Type: new Abstract: Graph RAG mitigates hallucinations and stale knowledge in LLMs, particularly for multi-hop question answering.

By Seonho An, Chaejeong Hyun, Min-Soo Kim

llms rag nlp safety

arXiv AI

Jul 23

Knowledge-Centric Self-Improvement

arXiv:2607. 19592v1 Announce Type: new Abstract: Self-improving AI systems typically treat the agent as the object that improves, by optimizing prompts, workflows, harnesses, or even the agent's own code.

By Xuefei Julie Wang, Lauren Hyoseo Yoon, Chengrui Qu, Amanda Zichang Wang, Atharva Sehgal, Eric Mazumdar, Yisong Yue

llms rag agents efficiency benchmarks

arXiv AI

Jul 23

Fidelity Before Structure: Verbatim Chunks Beat Lossy Artifact Extraction in Long-Conversation LLM Memory

arXiv:2601. 00821v4 Announce Type: replace Abstract: A growing class of conversational-memory systems compresses dialogue history into structured artifacts (extracted facts, decisions, or events) on the premise that distilled structure retrieves better than raw text.

By Tao An

llms rag efficiency benchmarks

arXiv Machine Learning

Jul 23

TempoNet: Slack-Quantized Transformer-Guided Reinforcement Scheduler for Adaptive Deadline-Centric Real-Time Dispatchs

arXiv:2602. 18109v3 Announce Type: replace Abstract: Real-time schedulers must reason about tight deadlines under strict compute budgets.

By Rong Fu, Yibo Meng, Zeyu Zhang, Ziming Guo, Jia Yee Tan, Xiaojing Du, Simon James Fong

llms rag nlp reinforcement-learning efficiency benchmarks

arXiv Machine Learning

Jul 23

Missing-by-Design: Certifiable Modality Deletion for Revocable Multimodal Sentiment Analysis

arXiv:2602. 16144v4 Announce Type: replace-cross Abstract: As multimodal systems increasingly process sensitive personal data, the ability to selectively revoke specific data modalities has become a critical requirement for privacy compliance and user autonomy.

By Rong Fu, Ziming Wang, Chunlei Meng, Jiekai Wu, Kangan Qian, Hao Zhang, Simon Fong

rag nlp multimodal benchmarks safety

arXiv AI

Jul 23

HyGRL: Adaptive Hybrid Graph Reasoning for Multi-Entity Questions

arXiv:2607. 19398v1 Announce Type: new Abstract: Multi-entity compositional questions pose significant challenges to existing retrieval-augmented language models.

By Junyi Wang

llms rag reinforcement-learning efficiency benchmarks

arXiv AI

Jul 23

Cross-Subject Semantic Decoding with Shared-Space Alignment for Generalized Neural Representation Learning

arXiv:2607. 19394v1 Announce Type: cross Abstract: Generalizing across subjects remains challenging in invasive neural recordings because electrode configurations, anatomical structures, and neural signal patterns vary substantially across individuals.

By Ji-Hoon Heo, Aleksandra Joanna Wisniewska, Seo-Hyun Lee, Seong-Whan Lee

rag diffusion safety

arXiv AI

Jul 23

Spectral-LSH: Sub-Quadratic Prompt Compression via Krylov-Projected Locality-Sensitive Hashing

arXiv:2607. 19368v1 Announce Type: new Abstract: Long-prompt inference remains expensive because prefill attention scales quadratically with sequence length.

By Ali Mahdavi, Azaseh Zamanifar, Amirfarhad Farhadi, Omid Kashefi

llms rag

arXiv Machine Learning

Jul 23

Reliability-Aware Hard--Soft Physics-Informed Neural Networks for Robust Learning of Challenging Partial Differential Equations

arXiv:2607. 19377v1 Announce Type: cross Abstract: Physics-informed neural networks (PINNs) provide a mesh-free framework for solving partial differential equations, but their training is often affected by loss imbalance, optimization stiffness, and difficulty in capturing localized or multi-mode solution structures.

By Duc Tien Nguyen, Hang Tran, Trinh Minh Tuan, Nguyen Duc Manh, Dinh Gia Ninh

rag

arXiv AI

Jul 23

Overview of FinMMEval 2026 Task 2: Multilingual Financial Short-Answer Question Answering

arXiv:2607. 19867v1 Announce Type: cross Abstract: FinMMEval 2026 Task 2 evaluates short-answer financial question answering over multilingual evidence.

By Zhuohan Xie, Xueqing Peng, Georgi Georgiev, Dimitar Dimitrov, Yuyang Dai, Rania Elbadry, Vanshikaa Jani, Lingfei Qian, Fan Zhang, Jimin Huang, Jiahui Geng, Yankai Chen, Ye Yuan, Haolun Wu, Yuxia Wang, Ivan Koychev, Veselin Stoyanov, Mingzi Song, Yu Chen, Xue Liu, Preslav Nakov

llms rag nlp benchmarks

arXiv Machine Learning

Jul 23

Tensor Network Machine Learning for Wildfire Susceptibility Mapping: from Grokking Dynamics to Quantum Mixedness of Class Representations

arXiv:2607. 19503v1 Announce Type: cross Abstract: A quantum-inspired tensor network framework for wildfire susceptibility classification in the Gargano region is introduced, leveraging AlphaEarth embeddings and Matrix Product State models.

By Domenico Pomarico, Alessandra Costantino, Gabriel Ramirez Sanchez, Loredana Bellantuono, Davide D' Al\`o, Mario Elia, Alessandro Fania, Francesco Giordano, Niloofar Kheirkhahan, Raffaele Lafortezza, Ester Pantaleo, Sabina Tangaro, Roberto Bellotti, Alfonso Monaco, Nicola Amoroso

rag

arXiv AI

Jul 23

Physics-Aware Complex-Valued State Space Model with Scattering-Prior Feature Modulation for PolSAR Image Classification

arXiv:2607. 19787v1 Announce Type: cross Abstract: Polarimetric synthetic aperture radar (PolSAR) image classification is a representative task for physics-aware GeoAI, where land-cover semantics are closely coupled with electromagnetic scattering mechanisms.

By Fangyan Zhang, Fan Zhang, Shiqi Zhou, Jun Ni, Carlos L\'opez-Mart\'inez, Qiang Yin

rag computer-vision benchmarks

arXiv Machine Learning

Jul 23

DREMnet: An Interpretable Denoising Framework for Semi-Airborne Transient Electromagnetic Signal

arXiv:2503. 22223v2 Announce Type: replace Abstract: The semi-airborne transient electromagnetic method (SATEM) is capable of conducting rapid surveys over large-scale and hard-to-reach areas.

By Shuang Wang, Ming Guo, Xuben Wang, Fei Deng, Lifeng Mao, Bin Wang, Wenlong Gao

llms rag safety

arXiv AI

Jul 23

SubQuad: Near-Quadratic-Free Structure Inference with Distribution-Balanced Objectives in Adaptive Receptor framework

arXiv:2602. 17330v5 Announce Type: replace-cross Abstract: Comparative analysis of adaptive immune repertoires at population scale is hampered by two practical bottlenecks: the near-quadratic cost of pairwise affinity evaluations and dataset imbalances that obscure clinically important minority clonotypes.

By Rong Fu, Zijian Zhang, Kun Liu, Jiekai Wu, Xianda Li, Simon Fong

rag efficiency multimodal safety

arXiv AI

Jul 23

Auditing Retrieval-Augmented LLM Hypotheses for Longitudinal Cell Painting Morphology

arXiv:2607. 19415v1 Announce Type: cross Abstract: High-content morphological profiling (Cell Painting) yields sensitive, high-dimensional signatures of cellular state, but translating longitudinal morphology trajectories into interpretable biology remains difficult, especially for weak, chronic perturbations such as low-dose-rate ionizing radiation.

By Gilchan Park, Guang Zhao, Byung-Jun Yoon, Shinjae Yoo

llms rag

arXiv Machine Learning

Jul 23

Geometry-Guided Generative Representation for Functional Brain Graphs

arXiv:2511. 04539v2 Announce Type: replace-cross Abstract: In network neuroscience, functional brain systems are often characterized using separate yet related graph-theoretic or spectral descriptors, overlooking how these properties covary and partially overlap across individuals and conditions.

By Subati Abulikemu, Tiago Azevedo, Michail Mamalakis, John Suckling

llms rag diffusion safety

arXiv AI

Jul 23

CGCE: Classifier-Guided Concept Erasure in Generative Models

arXiv:2511. 05865v3 Announce Type: replace-cross Abstract: Recent advancements in large-scale generative models have enabled the creation of high-quality images and videos, but have also raised significant safety concerns regarding the generation of unsafe content.

By Viet Nguyen, Vishal M. Patel

rag benchmarks safety

arXiv AI

Jul 23

Decodable but Not Detectable: A Leakage Fingerprint for Near-OOD Benchmarks

arXiv:2607. 19393v1 Announce Type: cross Abstract: While auditing a perturbation-based OOD detector on a document benchmark, we recorded an AUROC of 0.

By Vishnu Bindu Balachandran

rag benchmarks

arXiv AI

Jul 23

Reinforcement Learning for Large Language Model Selective Evidence Adoption from Contaminated Retrieval Results

arXiv:2607. 20090v1 Announce Type: cross Abstract: Retrieval-augmented large language models frequently face contexts that interleave useful evidence with misleading statements or instruction-like content.

By Yanyu Chen, Yue Li, Yongyi Cui, Dongsheng Shi, Lichang Dai

llms rag reinforcement-learning benchmarks

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