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

Oct 15

Learning Graph Energies for Finite-Time Generation

arXiv:2610.19946v1 Announce Type: new Abstract: Energy-based models can represent distributions over discrete structures such as molecular graphs, but an energy that is accurate at equilibrium need n...

By Amartya Banerjee, Xingyu Xu, Caroline Moosm\"uller, Harlin Lee

rag

arXiv AI

Oct 15

Co-adaptive Rule Routing and Constraining for Structured Knowledge Retrieval

arXiv:2610.14465v1 Announce Type: cross Abstract: Structured knowledge retrieval acquires task-relevant evidence from structured knowledge sources for downstream tasks. Existing methods rely on uncon...

By Zhisheng Qi, Haoyu Han, Jiaxi Li, Bing He, Huiyuan Chen, Franck Dernoncourt, Ryan A. Rossi, Mahantesh M. Halappanavar, Jin Lu, Yu Zhang, Tianming Liu, Yu Wang

rag agents reinforcement-learning fine-tuning

arXiv AI

Oct 15

The Tokens Strike Back: Safety-Aware Denoising with Directional Embedding-based Revision

arXiv:2610.17636v1 Announce Type: cross Abstract: The Safety-Aware Denoiser (SAD) is a recent, training-free, safety-guidance framework for text diffusion models. During inference, SAD steers text sa...

By Amman Yusuf, Jiwoo Shin, Ruizhi Deng, Heitor Rodrigues Guimar\~{a}es, Nikita Dvornik, Mijung Park

llms rag diffusion safety

arXiv AI

Oct 15

What DNA Foundation Models Learn Beyond Sequence Composition

arXiv:2610.15711v1 Announce Type: cross Abstract: Do genomic foundation models (FMs) provide predictive information beyond simple sequence composition? We evaluate frozen representations from five DN...

By Vincenzo Yuto Civale, Andrew David Bagdanov, Alberto Magi

rag fine-tuning

arXiv AI

Oct 15

Benchmarking Quantum Kernel SVMs for Credit Card Fraud Detection: Performance Realities Under NISQ Constraints

arXiv:2610.17027v1 Announce Type: new Abstract: Detecting credit card fraud is notoriously difficult because fraudulent charges make up less than 0.2% of total transactions. Quantum Machine Learning...

By Hitanshi Arora, Mohit Swarnkar, Aswani Kumar Cherukuri

rag benchmarks

arXiv AI

Oct 15

Siam-ALS: An Explainable Siamese Deep Learning Framework for Early ALS Detection Using EEG and Eye-Tracking Signals

arXiv:2610.15351v1 Announce Type: cross Abstract: Amyotrophic lateral sclerosis (ALS) diagnosis remains challenging due to heterogeneous symptoms and reliance on clinical assessment, underscoring the...

By Abdur Rahman, A. A. M. Muzahid, Istiak Ahmed, Dipto Biswas, Hua Han, Yujin Zhang, Ferdous Sohel

rag multimodal safety

arXiv Machine Learning

Oct 15

Gap Detection: Mitigating Homogenization through Demand and Defensibility

arXiv:2610.20162v1 Announce Type: cross Abstract: Language models often produce semantically similar answers to open-ended questions, even when many plausible alternatives exist. Generating useful al...

By Xucheng Yu, Haibo Jin, Xiaoqi Wang, Runze Kong, Haohan Wang

llms rag

arXiv AI

Oct 15

Controllable Diverse Sampling through Pullback Directions

arXiv:2610.14294v1 Announce Type: new Abstract: Conditional diffusion models can generate high-quality images that align closely with a given prompt. However, samples generated from different random...

By Sylvain Dehayem Kenfouo, Aaron Zweig, Mingxuan Zhang, Elham Azizi

rag diffusion safety

arXiv AI

Oct 15

History Replays Itself: Unleashing Long-Context Capability in Linear Attention

arXiv:2610.15715v1 Announce Type: new Abstract: Linear attention promises the efficiency needed for long-context language modelling, yet its fixed-size recurrent state must simultaneously support ong...

By Li Nanbo, Firas Laakom, Yilan Zhang, Piotr Pi\k{e}kos, Yimeng Chen, Liangyu Wang, Yifan Xu, Mateusz Ostaszewski, Dandan Guo, Wenyi Wang, Yanning Dai, Yuhui Wang, J\"{u}rgen Schmidhuber

llms rag efficiency

arXiv AI

Oct 15

LATCH: LLM-Assisted Timing Closure Harness for Post-Route FPGA Optimisation

arXiv:2610.16625v1 Announce Type: new Abstract: Post-route FPGA timing closure remains expert-dependent and computationally expensive. We present LATCH (LLM-Assisted Timing Closure Harness), a two-la...

By Shu Gu, Matthew Youngman, Yuqin Zhao, Cristian Sestito, Ali Siddique, Ramesh Krishnamurthy, Danial Chitnis, Themis Prodromakis

llms rag agents

arXiv AI

Oct 15

Configuring RAG Systems: What Breaks, Where Originates, and How to Fix

arXiv:2610.18567v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) has emerged as a dominant paradigm for improving Large Language Model (LLM) by intertwining it with other componen...

By Liangyu Chen, Youpeng Ma, Yulong Ye, Zezhen Xiang, Tao Chen

llms rag

arXiv AI

Oct 15

Read the Room Before Your Model Generates

arXiv:2610.18820v2 Announce Type: new Abstract: Large language models (LLMs) generally rely on sampling temperature to regulate the amount of randomness in their outputs. Mainstream methods for selec...

By Muyao Kong, Zhihao Lin

llms rag

arXiv AI

Oct 15

Embedding Information in Policy Randomness: Distribution-Preserving Implicit Communication in MDPs

arXiv:2610.15976v1 Announce Type: cross Abstract: This paper investigates a new role of randomness in stochastic policies--as a medium for embedding and communicating information. Specifically, we co...

By Gongpu Chen, Deniz G\"und\"uz

rag agents

arXiv AI

Oct 15

AutoSec-RAN: Specification-Grounded LLM Fine-Tuning for Automated Security Analysis of O-RAN

arXiv:2610.15995v1 Announce Type: cross Abstract: This paper presents AutoSec-RAN, a specification-grounded large language model (LLM) framework for automated security triage of Open Radio Access Net...

By Anoop Mishra, Joshua Moore, Aly Sabri Abdalla, Vuk Marojevic

llms rag fine-tuning

arXiv AI

Oct 15

EarthAlign: Learning Language-Aligned Representations of Earth System Data

arXiv:2610.14624v1 Announce Type: cross Abstract: Interpreting Earth system conditions is central to understanding environmental risks and informing decisions across weather- and climate-sensitive se...

By Fadillah Adamsyah Maani, Numan Saeed, Jiaqi Ma, Dat Tien Nguyen, Youssef Wehbe, Duncan Watson-Parris, Salman Khan

rag nlp multimodal safety

arXiv AI

Oct 15

A Sovereign, Indic-First, Reasoning Model

arXiv:2610.15371v1 Announce Type: cross Abstract: Gnani-Evon-v3.3-30B-A3B is a long-context hybrid Mamba-Transformer mixture-of-experts model for reasoning, instruction following, and tool use in Eng...

By Sutanshu Saksena Raj, Prasanjith Pasunuti, Parijat Chatterjee, Daksh Maan, Purusharth Malik, Nayanjit Sarkar, Avinash Benki

llms rag agents nlp reinforcement-learning efficiency benchmarks

arXiv AI

Oct 15

Hyperbolic Time Series Forecasting with Learnable Decomposition and Manifold Dynamics

arXiv:2610.15760v1 Announce Type: cross Abstract: Multiscale structure is central to time series forecasting: temporal signals contain slowly varying trends, intermediate seasonal patterns, and high-...

By Sarang Rajendra Patil, Vishal Fenn, Mengjia Xu

rag benchmarks

arXiv AI

Oct 15

Personalized LLM Recommendation with Semantic IDs: Autoregressive Beam Search vs. Multi-Token Prediction

arXiv:2610.15864v1 Announce Type: cross Abstract: Large-scale personalization is shifting from embedding-table retrieval to LLM-based recommenders that generate the Semantic ID (SID) of the item to r...

By Sejoon Oh, Fernando Amat Gil, Evan Smothers, Dan Iter, Mark Thornburg, Dawit Mureja Argaw, Sourabh Medapati, Thea Wang, Ria Verma, Qiuling Xu, Harshit Syal, Ehsan Gholami, Moumita Bhattacharya, Ashish Rastogi

llms rag reinforcement-learning efficiency

arXiv AI

Oct 15

Know-Thy-Not: Training-Free Targeted Negation in Dual-Encoder Vision-Language Models

arXiv:2610.17440v1 Announce Type: cross Abstract: Dual-encoder vision-language models systematically fail at negation, scoring ''a cat without a dog'' nearly identically to ''a cat with a dog.'' We s...

By DoYoung Kim, Changkyu Choi, Ad\'in Ram\'irez Rivera, YunSeok Choi, Jee-Hyong Lee

llms rag multimodal benchmarks

arXiv AI

Oct 15

Foundation Models for Event Prediction Across Heterogeneous Event Logs

arXiv:2610.17503v1 Announce Type: cross Abstract: Event logs are ubiquitous across real-world domains, including business processes, manufacturing workflows, healthcare, and many other operational sy...

By Fabian Spaeh, Sean Jaffe, Shandian Zhe, Bin Shen

rag

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