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

Aug 5

Asking Questions the Right Way: A Multi-Agent Conversational System for Prompt Formulation in Complex Task Resolution

arXiv:2608. 01366v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are integral to complex intellectual tasks, yet output quality remains constrained by user-provided prompts.

By B. Sankar, Pawni Yadav, Srinidhi Ranjini Girish, Amogh A. S

llms rag agents

arXiv Machine Learning

Aug 5

Task-Oriented Candidate-Latent Feedback for Coarse-to-Fine Sensing in Distributed OFDM-ISAC Networks

arXiv:2608. 03319v1 Announce Type: cross Abstract: Future integrated sensing and communication (ISAC) architectures separate the sensing entity (SE) that acquires measurements from the sensing function (SF) that performs inference, creating a need for compact, task-oriented feedback on the SE-SF interface.

By Shiv Shankar, Radha Krishna Ganti, J Klutto Milleth

rag efficiency

arXiv AI

Aug 5

MemArena: An Ego-Centric Benchmark for On-Device Agentic Personal Memory Assistants at Scale

arXiv:2608. 02613v1 Announce Type: cross Abstract: Edge-deployed personal memory assistants must handle private interpersonal conversations on-device with open-weight models.

By Jiadong Zhang, Xiaosong Ma

rag agents benchmarks data-engineering

arXiv AI

Aug 5

HyperFL: Query-Adaptive Representation Learning for Software Fault Localization

arXiv:2608. 02967v1 Announce Type: cross Abstract: Software fault localization identifies the code locations responsible for reported issues and is a fundamental step toward automated debugging and program repair.

By Shuai Shao, Yiming Zeng, Yu Zhao, Tingting Yu

rag fine-tuning benchmarks

arXiv AI

Aug 5

Lean Refactor: Multi-Objective Controllable Proof Optimization via Agentic Strategy Search

arXiv:2605. 20244v2 Announce Type: replace-cross Abstract: We present Lean Refactor, a plug-and-play retrieval-augmented agentic framework for multi-objective, controllable, and version-robust refactoring of Lean proofs.

By Jialin Lu, Soonho Kong, Rodrigo Stehling, Kaiyu Yang, Zhangyang Wang, Weiran Sun, Wuyang Chen

llms rag agents fine-tuning benchmarks

arXiv AI

Aug 5

Beyond Representational Similarity: Source-Conditioned Description-Length Gain for Generative Plagiarism Detection and Candidate Source Reranking

arXiv:2608. 03859v1 Announce Type: cross Abstract: Large language models (LLMs) pose challenges to academic integrity and peer review.

By Peijia Guo, Wenxuan Xie, ZiGuang Li, Ming Li

llms rag benchmarks

arXiv Machine Learning

Aug 5

DAIF: A Data-Driven Intermediate Fusion Framework for Multimodal Supervised Learning via Approximate Message Passing

arXiv:2608. 02769v1 Announce Type: cross Abstract: Multimodal supervised learning seeks to leverage multiple heterogeneous data sources to improve predictive performance.

By Sagnik Nandy, Samriddha Lahiry, Pragya Sur, Subhabrata Sen

rag multimodal benchmarks

arXiv Machine Learning

Aug 5

Bi-semantic Chemical Embedder for Joint Representation Learning of SMILES and Natural Language

arXiv:2608. 03855v1 Announce Type: new Abstract: Transformer models have revolutionized natural language processing (NLP), and text-based molecular representations like SMILES have successfully extended these architectures to chemistry.

By David Ming Segura, Jeremy Goumaz, Joshua W. Sin, Bojana Rankovi\'c, Philippe Schwaller

llms rag nlp

arXiv Machine Learning

Aug 5

Beyond Initialization Loss: A Systematic Study of Token Embedding Initialization Strategies for LLM Vocabulary Extension

arXiv:2608. 03494v1 Announce Type: cross Abstract: Vocabulary extension is an efficient way to adapt pretrained large language models (LLMs) to new languages, but the initialization of newly added token embeddings can strongly affect continued pre-training (CPT) efficiency.

By Raviraj Joshi, Utkarsh Vaidya, Sanjay Singh Chauhan, Niranjan Wartikar

llms rag

arXiv Machine Learning

Aug 5

SimulRAG: Simulator-based RAG for Grounding LLMs in Long-form Scientific QA

arXiv:2509. 25459v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) show promise in generating long-form scientific explanations that synthesize evidence and connect multiple factors.

By Haozhou Xu, Dongxia Wu, Matteo Chinazzi, Ruijia Niu, Rose Yu, Yi-An Ma

llms rag nlp benchmarks

arXiv AI

Aug 5

Large Language Models provide support for the parallelogram theory of analogy

arXiv:2603. 19066v2 Announce Type: replace-cross Abstract: Four-term word analogies (A:B::C:D) are classically modeled geometrically as parallelograms: adding the vector B-A+C produces D.

By Qiawen Ella Liu, Raja Marjieh, Jian-Qiao Zhu, Adele E. Goldberg, Thomas L. Griffiths

llms rag fine-tuning safety

arXiv AI

Aug 5

Training Documents Reranker with Search Rubrics for Deep Research Agent

arXiv:2608. 03527v1 Announce Type: cross Abstract: Retrieval systems help deep research agents generate high-quality answers by providing relevant documents.

By Wenhan Liu, Yu Lu, Qiaolin Xia, Hui Xu, Tong Zhao, Jian Xi, Yutao Zhu, Haijin Liang, Haibo Shi, Hao Wang, Zhicheng Dou

llms rag agents reinforcement-learning fine-tuning benchmarks

arXiv AI

Aug 5

Dr. AGENTONOMICS: A Didactic Experiment of AGENTONOMICS

arXiv:2608. 03524v1 Announce Type: new Abstract: AGENTONOMICS is a framework that treats AI agents as economic entities that can be designed, managed, and governed through an integrated management architecture.

By Fengjunjie Pan, Alois Knoll

rag agents multimodal

arXiv AI

Aug 5

A Hierarchical Approach to Imitation Learning for Manipulation Tasks Requiring Time Varying Forces

arXiv:2608. 03103v1 Announce Type: cross Abstract: Diffusion policies have shown strong performance in learning complex, multi-modal behaviors for robotic manipulation.

By Rishabh Shukla, Adithya Santhosh, Shaili Gandhi, Samrudh Moode, Satyandra K. Gupta

rag diffusion robotics multimodal benchmarks

arXiv AI

Aug 5

DocTrace: Towards Traceable Long Document VQA via Hierarchical Evidence Graph Reasoning

arXiv:2608. 03292v1 Announce Type: new Abstract: Long Document Visual Question Answering (LongDocVQA) requires Multimodal Large Language Models (MLLMs) to locate, integrate, and reason over heterogeneous document elements distributed across multiple pages.

By Le Xiang, Zhicheng Guan, Hong Chen, Xiaocong Lin, Zhenghua Lei, Teng Hu, Bolei He, Long Zeng

llms rag agents nlp fine-tuning multimodal benchmarks

arXiv AI

Aug 5

Adaptive Two-Stage Visual Token Pruning for Efficient Inference in Video-Language Models

arXiv:2608. 03112v1 Announce Type: cross Abstract: Vision-language models excel at image and video understanding but suffer from high inference latency due to the need to process thousands of tokens per image, limiting their deployment on resource-constrained edge devices and in real-time surveillance applications.

By Paribesh Regmi, Qingshuang Chen, Chi Zhang, Heba Aly, Yelin Kim, Hongda Mao

llms rag fine-tuning efficiency multimodal benchmarks

arXiv AI

Aug 5

Distractor-Aware Truncation: Disentangling Context-Length Effects from Signal Loss in Long-Context LLM Benchmarks

arXiv:2608. 03297v1 Announce Type: new Abstract: A standard claim in the literature on retrieval-augmented and memory-augmented language models is that shorter context is better when the relevant information is preserved.

By Mohsen Arjmandi

llms rag benchmarks

arXiv Machine Learning

Aug 5

ATFlash: Per-RoPE-Wavelength Attention Windows for Compute/Memory-Efficient LLM Inference

arXiv:2608. 02947v1 Announce Type: new Abstract: The attention score with rotary position embeddings (RoPE) decomposes exactly into a sum over its 2D-rotation frequency pairs, and each pair's wavelength limits how far it can discriminate position.

By Shun-ichiro Hayashi, Daichi Mukunoki, Tetsuya Hoshino, Takahiro Katagiri

llms rag efficiency benchmarks

arXiv AI

Aug 5

When Outputs Disperse, Does Epistemic Revision Follow? A Black-Box Coupling Diagnostic for Machine Collectives

arXiv:2608. 03722v1 Announce Type: new Abstract: Collective intelligence research treats disagreement as evidence of epistemic diversity: if agents express different views, the group should retain capacity to revise.

By Molood Arman

llms rag agents

arXiv AI

Aug 5

From Generator to Embedder: Harnessing Innate Abilities of Multimodal LLMs via Building Zero-Shot Discriminative Embedding Model

arXiv:2508. 00955v3 Announce Type: replace-cross Abstract: Adapting generative Multimodal Large Language Models (MLLMs) into universal embedding models typically demands resource-intensive contrastive pre-training, while traditional hard negative mining methods suffer from severe false negative contamination.

By Yeong-Joon Ju, Seong-Whan Lee

llms rag fine-tuning multimodal benchmarks