arXiv AI
Oct 15
Belief Embedding Tree Search
arXiv:2610.15046v1 Announce Type: new Abstract: Beliefs in a Partially Observable Markov Decision Process (POMDP) are posterior distributions over the hidden state given the agent's history of action...
Retrieval-augmented generation
Retrieval pipelines, vector search, chunking and reranking: how models are grounded in a corpus instead of their weights.
arXiv AI
Oct 15
OntoAR-HAR: Ontology-Guided Agentic RAG with Personalized Memory for Human Activity Recognition
arXiv:2610.15292v1 Announce Type: new Abstract: LLMs increasingly support sensor-based human activity recognition (HAR) by linking motion signals with activity semantics and physical knowledge. Retri...
arXiv AI
Oct 15
CHEAR: Confusion-Hierarchy Evidence-Aware Reasoning for Cost-Efficient Human Activity Recognition
arXiv:2610.15298v1 Announce Type: new Abstract: Large language models (LLMs) offer a new approach to wearable-sensor-based human activity recognition. Retrieval-augmented generation (RAG) further int...
arXiv AI
Oct 15
GAMW: Generation-Aware Mel-Domain Watermarking for TTS Traceability
arXiv:2610.15082v1 Announce Type: cross Abstract: As text-to-speech (TTS) systems continue to advance, provenance tracking and security verification of synthesized speech have become increasingly imp...
arXiv AI
Oct 15
Joint Embedding with Dynamic Integration network (JEDI-net)
arXiv:2610.17314v1 Announce Type: cross Abstract: Deep learning has become the dominant form of machine learning due in part, to its ability to automatically engineer complex meta features from data....
arXiv Computation and Language
Oct 15
ConRAG: Consensus-Driven Evidence Flow for Multi-Hop Question Answering
arXiv:2605.28093v3 Announce Type: replace Abstract: Retrieval-augmented generation (RAG) has emerged as a promising paradigm for enhancing large language models (LLMs) on multi-hop question answering...
arXiv Machine Learning
Oct 15
Embedding Geometry Shapes LLM Routing: Tracing Failure Modes and Improving Generalization
arXiv:2610.19198v1 Announce Type: cross Abstract: With the growing number of LLMs available, selecting which one to use for a prompt has become a key question. A large part of the routing literature...
arXiv AI
Oct 15
Unsupervised Data Drift Monitoring for Deployed Deepfake Speech Detectors
arXiv:2610.16826v1 Announce Type: cross Abstract: Deepfake speech detectors are typically evaluated as binary classifiers on fixed benchmarks, but deployed systems face evolving attacks, codecs, spea...
arXiv AI
Oct 15
Large Language Models Extend Known Research But Do Not Create New Research Directions
arXiv:2610.17439v1 Announce Type: new Abstract: The success of autonomous research systems relies on the quality of the scientific hypotheses they generate. Recent studies report that human reviewers...
arXiv AI
Oct 15
World Modeling through Spectral Alignment
arXiv:2610.15429v1 Announce Type: cross Abstract: How do we tell a world model what information to preserve? We study this question through the lens of spectral representation learning. We introduce...
arXiv Computation and Language
Oct 15
Analyzing performance of Retrieval Augmented Generation models for Question Answering Tasks
arXiv:2610.20419v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) models have become almost a cornerstone of open-domain question answering tasks; in which the quality of answers g...
arXiv AI
Oct 15
LeHami: Symplectic Latent Dynamics for World Models
arXiv:2610.15267v1 Announce Type: cross Abstract: Joint-embedding predictive architectures (JEPAs) learn world models directly in latent space, but unconstrained autoregressive predictors may contrac...
arXiv AI
Oct 15
ARMED: Adaptive Retrieval-Augmented Medication Recommendation
arXiv:2610.16440v1 Announce Type: cross Abstract: Medication recommendation requires jointly considering diagnoses, comorbidities, longitudinal patient history, and treatment interactions. Although r...
arXiv AI
Oct 15
Budgeted KV-Cache Repair for Evolving Contexts
arXiv:2610.17338v1 Announce Type: new Abstract: Language-model agents revise their working context as information becomes obsolete, but deleting text does not erase its influence on cached computatio...
arXiv AI
Oct 15
Beyond Black Boxes: Visual Grounding for Text Embeddings
arXiv:2610.18047v1 Announce Type: new Abstract: In this paper, our goal is to represent text embeddings as sketches for three main reasons. First, to visualize text representation and to explore thei...
arXiv AI
Oct 15
Label-Centric Knowledge Retrieval for Zero-Shot Text Classification
arXiv:2610.16182v1 Announce Type: new Abstract: Flagship large language models (LLMs) offer rich general knowledge and strong reasoning capabilities, but their high inference cost and latency limit t...
arXiv AI
Oct 15
Complex materials engineering via Provenance Action Graphs: potential, structure and demonstration
arXiv:2610.18314v1 Announce Type: new Abstract: This work discusses and tests the potential of reaction graphs for material synthesis, in which events consist of reaction steps (actions) and their ou...
arXiv AI
Oct 15
Choosing LLMs for Strategic Agent Interactions
arXiv:2610.18354v1 Announce Type: new Abstract: Game-theoretic benchmarks claim that large language model (LLM) strategic decision-making varies across game types, interaction structures, and capabil...
arXiv AI
Oct 15
PixSearch: Region-Grounded Retrieval for Knowledgeable Large Multimodal Models
arXiv:2601.19060v2 Announce Type: replace-cross Abstract: Multimodal Retrieval-Augmented Generation (MM-RAG) augments visual question answering (VQA) with external knowledge, but many systems rely on...
arXiv Machine Learning
Oct 15
Universal Sample-Based Embeddings of Higher-Order Objects
arXiv:2610.19899v1 Announce Type: new Abstract: Neural networks operate naturally on finite-dimensional vectors, yet many problems require reasoning about higher-order objects such as distributions,...