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 Machine Learning

Jul 14

TOLiD: Bridging the Architecture Gap in Vision Foundation Model to LiDAR Pretraining via Token Lifting for Distillation

arXiv:2607. 10762v1 Announce Type: cross Abstract: Cross-modal distillation from Vision Foundation Models (VFMs) to LiDAR backbones has recently emerged as a self-supervised pretraining strategy that reduces reliance on dense point-wise annotation for 3D scene understanding.

By Sutharsan Mahendran, Darshana Priyasad, Kaushik Roy, Tharindu Fernando, Sridha Sridharan, Clinton Fookes, Peyman Moghadam

llms rag computer-vision efficiency multimodal

arXiv AI

Jul 14

Workload-Driven Optimization for On-Device Real-Time Subtitle Translation

arXiv:2607. 09957v1 Announce Type: cross Abstract: This report studies on-device English-to-Traditional-Chinese subtitle translation for Taiwan under short inputs, short outputs, batch-size-one inference, low latency, and privacy constraints.

By Tsz-To Wong

llms rag nlp fine-tuning efficiency benchmarks safety

arXiv AI

Jul 14

Coresets Before Score Sets: Evaluation-Unsupervised Prompt Subset Selection for LLM Benchmarks

arXiv:2607. 09739v1 Announce Type: new Abstract: We study LLM benchmark coreset selection: selecting a small subset of prompts over multiple benchmarks whose induced model scores and rankings approximate those obtained from the full benchmark suite.

By Jihan Yao, Gantavya Bhatt, Arnav Das, Peter Jin, Ke Bao, Qiaolin Yu, Khushi Bhardwaj, Chang Su, Jialei Wang, Yikai Zhu, Sugam Devare, Damon Mosk-Aoyama, Zhen Dong, Venkat Krishna Srinivasan, Yineng Zhang, Oleksii Kuchaiev, Jiantao Jiao, Banghua Zhu, Jeff Bilmes

llms rag benchmarks

arXiv AI

Jul 14

An Autonomous Scientific Knowledge Generation Framework for AI-Driven Scientific Discovery

arXiv:2607. 09806v1 Announce Type: cross Abstract: Artificial intelligence (AI) is transforming scientific discovery, but its effectiveness is fundamentally limited by the availability of structured scientific knowledge.

By Dibakar Datta

rag agents

arXiv AI

Jul 14

Time-Lag-Aware Deep Reinforcement Learning for Flexible Job-Shop Scheduling in PPVC Module Factories

arXiv:2607. 11725v1 Announce Type: cross Abstract: Prefabricated prefinished volumetric construction moves most building work into module factories, whose production floor operates as a flexible job shop.

By Ziheng Zhang, Wei Zhang

rag reinforcement-learning benchmarks

arXiv AI

Jul 14

Tool-Adaptive LLM Reranker

arXiv:2607. 10555v1 Announce Type: cross Abstract: Generative Large Language Models (LLMs) have revolutionized information retrieval, yet their strictly parametric nature frequently leads to severe factual hallucinations when confronted with complex queries beyond their epistemic boundaries.

By Zichuan Liu, Ruijin Hua

llms rag agents reinforcement-learning efficiency benchmarks safety

arXiv Machine Learning

Jul 14

NMIRacle: Multi-modal Generative Molecular Elucidation from IR and NMR Spectra

arXiv:2512. 19733v3 Announce Type: replace-cross Abstract: Molecular structure elucidation from spectroscopic data is a long-standing challenge in Chemistry, traditionally requiring expert interpretation.

By Federico Ottomano, Yingzhen Li, Alex M. Ganose

rag fine-tuning multimodal

arXiv AI

Jul 14

RAGU: A Multi-Step GraphRAG Engine with a Compact Domain-Adapted LLM

arXiv:2607. 11683v1 Announce Type: cross Abstract: Graph retrieval-augmented generation (GraphRAG) enhances large language models with structured knowledge, yet existing systems construct knowledge graphs in a single extraction pass, producing noisy entities and brittle retrieval.

By Mikhail Komarov, Ivan Bondarenko, Stanislav Shtuka, Oleg Sedukhin, Roman Shuvalov, Yana Dementyeva, Matvey Solovyov, Nikolay O. Nikitin

llms rag nlp

arXiv Machine Learning

Jul 14

Retrieval with Multiple Query Vectors through Anomalous Pattern Detection

arXiv:2605. 01965v2 Announce Type: replace Abstract: A classical vector retrieval problem typically considers a \emph{single} query embedding vector as input and retrieves the most similar embedding vectors from a vector database.

By Allassan Tchangmena A Nken, Baimam Boukar Jean Jacques, Miriam Rateike, Celia Cintas, Skyler Speakman

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arXiv AI

Jul 14

Graph Construction and Matching for Imperative Programs using Neural and Structural Methods

arXiv:2604. 26578v3 Announce Type: replace-cross Abstract: Reusing verification artefacts requires identifying structural and semantic similarities across programs and their specifications.

By Arshad Beg, Diarmuid O'Donoghue, Rosemary Monahan

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arXiv AI

Jul 14

First-Order Modal Logic in HOL: Deep and Shallow Embeddings with Automated Faithfulness (Extended Preprint)

arXiv:2607. 10880v1 Announce Type: new Abstract: We extend, in Isabelle/HOL, the deep-and-shallow embedding methodology of our prior work from propositional to first-order modal logic (FML) with constant-domain Kripke semantics.

By Christoph Benzm\"uller, Daniel Kirchner

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arXiv Machine Learning

Jul 14

Sticky Jump Diffusions: A Unifying View of Masked, Continuous, and Hybrid Diffusion

arXiv:2607. 10951v1 Announce Type: new Abstract: We introduce Sticky Jump Diffusions (SJDs), continuous-time Markov processes on $\mathbb R^d$ whose discrete anchors are token embeddings.

By Pascal Jutras-Dub\'e, Patrick Pynadath, Jeremy Lu, Yuan Gao, Ruqi Zhang

rag diffusion safety

arXiv AI

Jul 14

Physics-Informed Structure Anchoring With Capture-Aware Prototype Calibration for Cross-Environment RF Fingerprinting

arXiv:2607. 09760v1 Announce Type: cross Abstract: Radio frequency fingerprint identification (RFFI) uses transmitter-specific hardware imperfections as a physicallayer identity cue for Internet of Things (IoT) devices, but deep RFFI models often degrade when the acquisition environment changes.

By Fengchong Yao, Jianbing Li, Qing Liu, Qikun Liu, Kefeng Song, Haitao Li, Song Wang

rag benchmarks

arXiv AI

Jul 14

PhysMRV: Physical Memory Retrieval and Verification for Physics Plausibility Reasoning

arXiv:2607. 10190v1 Announce Type: cross Abstract: Video-language models (VLMs) have achieved remarkable performance on video understanding and visual question answering, yet they remain unreliable in reasoning about physical plausibility, where understanding object interactions, causal dynamics, and fundamental physical principles is essential.

By Wenyuan Wang, Lianyu Hu, Hao Wang, Yang Liu

llms rag nlp fine-tuning multimodal benchmarks

arXiv Machine Learning

Jul 14

A Risk-Field Enhanced Closed-Loop Digital Twin Framework for Autonomous Driving Safety Validation

arXiv:2607. 09772v1 Announce Type: cross Abstract: Autonomous driving systems require reliable safety validation before real-world deployment.

By Yongzhi Liu

rag agents reinforcement-learning robotics safety

arXiv AI

Jul 14

Graph-Based Bayesian Optimization for Quantum Circuit Architecture Search with Uncertainty Calibrated Surrogates

arXiv:2512. 09586v2 Announce Type: replace-cross Abstract: Quantum circuit design is a key bottleneck for practical quantum machine learning on complex, real-world data.

By Prashant Kumar Choudhary, Nouhaila Innan, Muhammad Shafique, Rajeev Singh

rag benchmarks

arXiv AI

Jul 14

GRASP: GRanularity-Aware Search Policy for Agentic RAG

arXiv:2607. 10463v1 Announce Type: new Abstract: Agentic retrieval-augmented generation (RAG) extends static RAG by allowing language models to iteratively reason, generate search queries, retrieve evidence, and predict answers.

By Varun Gandhi, Jaewook Lee, Shantanu Todmal, Franck Dernoncourt, Ryan Rossi, Zichao Wang, Andrew Lan

llms rag agents nlp reinforcement-learning benchmarks

arXiv Machine Learning

Jul 14

A Durability and Cross-Language Transfer Benchmark for a Validated Teaching-Feedback Classification Protocol

arXiv:2607. 11873v1 Announce Type: cross Abstract: Institutions collect far more open-ended teaching-evaluation feedback than they read.

By Esteban U. Vega Barajas

llms rag benchmarks

arXiv AI

Jul 14

More Structure, Not More Capacity: Object-Centric Representations for Visuomotor Imitation Learning

arXiv:2607. 09825v1 Announce Type: cross Abstract: Robotic manipulation policies rely on pre-trained vision models that give either a global scene embedding or a dense patch grid.

By Yi Li (TU Darmstadt), Alexandre Chapin (LIRIS), Liming Chen (LIRIS), Jan Peters (TU Darmstadt), Alap Kshirsagar (IIT Delhi, ADU)

rag robotics fine-tuning

arXiv AI

Jul 14

Towards Objective Dysgraphia Detection: A Multi-Branch Deep Learning Approach for Online Handwriting Analysis

arXiv:2607. 09826v1 Announce Type: cross Abstract: Dysgraphia is a specific learning disability that is prevalent among school-age children.

By Lydia Ouhib (LIASD), Yassine Ouzar (LIASD), Zo\'e Pinseel (LIASD), St\'ephane Bouilland (LIASD), Mehdi Ammi (LIASD)

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