Search: “retrieval”

Quantum Non-Linear Bandit Optimization

arXiv:2503.03023v2 Announce Type: replace Abstract: We study non-linear bandit optimization where the learner maximizes a black-box function with zeroth order function oracle, which has been successfu

applicationsarxiv-cs-lg

22 Apr 2026

Reasoning Over Space: Enabling Geographic Reasoning for LLM-Based Generative Next POI Recommendation

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DGX agent

arXiv:2601.04562v2 Announce Type: replace Abstract: Generative recommendation with large language models (LLMs) reframes prediction as sequence generation, yet existing LLM-based recommenders remain l

local-aiarxiv-cs-ai

22 Apr 2026

Towards Scalable Lifelong Knowledge Editing with Selective Knowledge Suppression

model-releasesarxiv-cs-ai

arXiv:2604.19089v1 Announce Type: new Abstract: Large language models (LLMs) require frequent knowledge updates to reflect changing facts and mitigate hallucinations. To meet this demand, lifelong kno

22 Apr 2026

What’s new in the Agentic Data Cloud: Powering the System of Action

model-releasesgoogle-cloud-ai

Companies are shifting from gen AI that simply answers questions to autonomous agents that perceive, reason, and act on their behalf. Attempting to scale these agents on legacy stacks exposes structur

22 Apr 2026

3 new ways Ads Advisor is making Google Ads safer and faster

Ads Advisor is an agentic conversational experience built with Gemini in Google Ads designed to help maximize performance based on business goals. The tool can help users get personalized answers, und

safetygoogle-ai

A Multi-Agent Approach for Claim Verification from Tabular Data Documents

arXiv:2604.17225v1 Announce Type: new Abstract: We present a novel approach for claim verification from tabular data documents. Recent LLM-based approaches either employ complex pretraining/fine-tunin

AnchorSeg: Language Grounded Query Banks for Reasoning Segmentation

arXiv:2604.18562v1 Announce Type: new Abstract: Reasoning segmentation requires models to ground complex, implicit textual queries into precise pixel-level masks. Existing approaches rely on a single

Brain-CLIPLM: Decoding Compressed Semantic Representations in EEG for Language Reconstruction

arXiv:2604.16370v1 Announce Type: new Abstract: Decoding natural language from non-invasive electroencephalography (EEG) remains fundamentally limited by low signal-to-noise ratio and restricted infor

Brain-Inspired Capture: Evidence-Driven Neuromimetic Perceptual Simulation for Visual Decoding

arXiv:2604.17927v1 Announce Type: new Abstract: Visual decoding of neurophysiological signals is a critical challenge for brain-computer interfaces (BCIs) and computational neuroscience. However, curr

CanonSLR: Canonical-View Guided Multi-View Continuous Sign Language Recognition

arXiv:2604.18184v1 Announce Type: new Abstract: Continuous Sign Language Recognition (CSLR) has achieved remarkable progress in recent years; however, most existing methods are developed under single-

applicationsarxiv-cs-cv

CaTS-Bench: Can Language Models Describe Time Series?

arXiv:2509.20823v5 Announce Type: replace-cross Abstract: Time series captioning, the task of describing time series in natural language, requires numeric and temporal reasoning, trend interpretation,

CFSR: Geometry-Conditioned Shadow Removal via Physical Disentanglement

arXiv:2604.18032v1 Announce Type: new Abstract: Traditional shadow removal networks often treat image restoration as an unconstrained mapping, lacking the physical interpretability required to balance

CLAG: Adaptive Memory Organization via Agent-Driven Clustering for Small Language Model Agents

arXiv:2603.15421v2 Announce Type: replace Abstract: Large language model agents heavily rely on external memory to support knowledge reuse and complex reasoning tasks. Yet most memory systems store ex

Concurrent Criterion Validation of a Validity Screen for LLM Confidence Signals via Selective Prediction

arXiv:2604.17716v1 Announce Type: new Abstract: The validity screen (Cacioli, 2026d, 2026e) classifies LLM confidence signals as Valid, Indeterminate, or Invalid. We test whether these classifications

CT Open: An Open-Access, Uncontaminated, Live Platform for the Open Challenge of Clinical Trial Outcome Prediction

arXiv:2604.16742v1 Announce Type: cross Abstract: Scientists have long sought to accurately predict outcomes of real-world events before they happen. Can AI systems do so more reliably? We study this

applicationsarxiv-cs-cl

Decision-Aware Attention Propagation for Vision Transformer Explainability

arXiv:2604.18094v1 Announce Type: new Abstract: Vision Transformers (ViTs) have become a dominant architecture in computer vision, yet their prediction process remains difficult to interpret because i

Decisive: Guiding User Decisions with Optimal Preference Elicitation from Unstructured Documents

arXiv:2604.18122v1 Announce Type: new Abstract: Decision-making is a cognitively intensive task that requires synthesizing relevant information from multiple unstructured sources, weighing competing f

Don't Adapt Small Language Models for Tools; Adapt Tool Schemas to the Models

arXiv:2510.07248v3 Announce Type: replace Abstract: Small language models (SLMs) enable scalable tool-augmented multi-agent systems where multiple SLMs handle subtasks orchestrated by a powerful coord

E2E-GMNER: End-to-End Generative Grounded Multimodal Named Entity Recognition

arXiv:2604.17319v1 Announce Type: cross Abstract: Grounded Multimodal Named Entity Recognition (GMNER) aims to jointly identify named entity mentions in text, predict their semantic types, and ground

Early life may have breathed oxygen earlier than believed

Around 2.3 billion years ago, a pivotal period known as the Great Oxidation Event set the evolutionary course for oxygen-breathing life on Earth. But MIT geobiologists and colleagues have found eviden

tutorialsmit-tech-review

Follow the Path: Reasoning over Knowledge Graph Paths to Improve Large Language Model Factuality

arXiv:2505.11140v3 Announce Type: replace Abstract: We introduce fs1, a simple yet effective method that improves the factuality of reasoning traces by collecting them from large reasoning models and

GraSP: Graph-Structured Skill Compositions for LLM Agents

arXiv:2604.17870v1 Announce Type: new Abstract: Skill ecosystems for LLM agents have matured rapidly, yet recent benchmarks show that providing agents with more skills does not monotonically improve p

local-aiarxiv-cs-cl

IDOBE: Infectious Disease Outbreak forecasting Benchmark Ecosystem

model-releasesarxiv-cs-lg

arXiv:2604.18521v1 Announce Type: new Abstract: Epidemic forecasting has become an integral part of real-time infectious disease outbreak response. While collaborative ensembles composed of statistica

iDocV2: Leveraging Self-Supervision and Open-Set Detection for Improving Pattern Spotting in Historical Documents

arXiv:2604.16726v1 Announce Type: new Abstract: Considering the imminent massification of digital books, it has become critical to facilitate searching collections through graphical patterns. Current

LLaMA-XR: A Novel Framework for Radiology Report Generation using LLaMA and QLoRA Fine Tuning

arXiv:2506.03178v2 Announce Type: replace-cross Abstract: Automated radiology report generation holds significant potential to reduce radiologists' workload and enhance diagnostic accuracy. However, g

LLM as Graph Kernel: Rethinking Message Passing on Text-Rich Graphs

arXiv:2603.14937v2 Announce Type: replace-cross Abstract: Text-rich graphs, which integrate complex structural dependencies with abundant textual information, are ubiquitous yet remain challenging for

LLMAR: A Tuning-Free Recommendation Framework for Sparse and Text-Rich Industrial Domains

arXiv:2604.16379v1 Announce Type: cross Abstract: Industrial B2B applications (e.g., construction site risk prediction, material procurement) face extreme data sparsity yet feature rich textual intera

Mammo-FM: Breast-specific foundational model for Integrated Mammographic Diagnosis, Prognosis, and Reporting

arXiv:2512.00198v2 Announce Type: replace Abstract: Breast cancer is one of the leading causes of death among women worldwide. We introduce Mammo-FM, the first foundation model specifically for mammog

safetyarxiv-cs-cv

MetaMem: Evolving Meta-Memory for Knowledge Utilization through Self-Reflective Symbolic Optimization

arXiv:2602.11182v2 Announce Type: replace Abstract: Existing memory systems enable Large Language Models (LLMs) to support long-horizon human-LLM interactions by persisting historical interactions bey

tutorialsarxiv-cs-cl

Modular Representation Compression: Adapting LLMs for Efficient and Effective Recommendations

arXiv:2604.18146v1 Announce Type: cross Abstract: Recently, large language models (LLMs) have advanced recommendation systems (RSs), and recent works have begun to explore how to integrate LLMs into i

tutorialsarxiv-cs-cl

MoE-nD: Per-Layer Mixture-of-Experts Routing for Multi-Axis KV Cache Compression

arXiv:2604.17695v1 Announce Type: cross Abstract: KV cache memory is the dominant bottleneck for long-context LLM inference. Existing compression methods each act on a single axis of the four-dimensio

MoRI: Learning Motivation-Grounded Reasoning for Scientific Ideation in Large Language Models

arXiv:2603.19044v2 Announce Type: replace Abstract: Scientific ideation aims to propose novel solutions within a given scientific context. Existing LLM-based agentic approaches emulate human research

Multimodal Policy Internalization for Conversational Agents

arXiv:2510.09474v2 Announce Type: replace Abstract: Modern conversational agents like ChatGPT and Alexa+ rely on predefined policies specifying metadata, response styles, and tool-usage rules. As thes

safetyarxiv-cs-cl

Multimodal Sentiment Analysis with Missing Modality: A Knowledge-Transfer Approach

arXiv:2401.10747v5 Announce Type: replace-cross Abstract: Multimodal sentiment analysis aims to identify the emotions expressed by individuals through visual, language, and acoustic cues. However, mos

Neuro-Symbolic Resolution of Recommendation Conflicts in Multimorbidity Clinical Guidelines

arXiv:2604.17340v1 Announce Type: new Abstract: Clinical guidelines, typically developed by independent specialty societies, inherently exhibit substantial fragmentation, redundancy, and logical contr

NIM4-ASR: Towards Efficient, Robust, and Customizable Real-Time LLM-Based ASR

arXiv:2604.18105v1 Announce Type: cross Abstract: Integrating large language models (LLMs) into automatic speech recognition (ASR) has become a mainstream paradigm in recent years. Although existing L

One of the most jarring things about current AI is its lack of introspection ability and metacognition. It doesn't know what it doesn't know…

researchfrancois-chollet--x

One of the most jarring things about current AI is its lack of introspection ability and metacognition. It doesn't know what it doesn't know, how it knows, or how it could find out. It's a one-way sys

ReCoQA: A Benchmark for Tool-Augmented and Multi-Step Reasoning in Real Estate Question and Answering

arXiv:2604.17944v1 Announce Type: new Abstract: Developing agents capable of navigating fragmented, multi-source information remains challenging, primarily due to the scarcity of benchmarks reflecting

RePrompT: Recurrent Prompt Tuning for Integrating Structured EHR Encoders with Large Language Models

arXiv:2604.17725v1 Announce Type: new Abstract: Large Language Models (LLMs) have shown strong promise for mining Electronic Health Records (EHRs) by reasoning over longitudinal clinical information t

tutorialsarxiv-cs-cl

ResearchBench: Benchmarking LLMs in Scientific Discovery via Inspiration-Based Task Decomposition

arXiv:2503.21248v3 Announce Type: replace Abstract: Large language models (LLMs) have shown potential in assisting scientific research, yet their ability to discover high-quality research hypotheses r

TeMuDance: Contrastive Alignment-Based Textual Control for Music-Driven Dance Generation

arXiv:2604.17005v1 Announce Type: new Abstract: Existing music-driven dance generation approaches have achieved strong realism and effective audio-motion alignment. However, they generally lack semant

safetyarxiv-cs-cv

The Provenance Gap in Clinical AI: Evidence-Traceable Temporal Knowledge Graphs for Rare Disease Reasoning

arXiv:2604.17114v1 Announce Type: new Abstract: Frontier large language models generate clinically accurate outputs, but their citations are often fabricated. We term this the Provenance Gap. We teste

safetyarxiv-cs-cl

Towards Intelligent Legal Document Analysis: CNN-Driven Classification of Case Law Texts

arXiv:2604.17674v1 Announce Type: new Abstract: Legal practitioners and judicial institutions face an ever-growing volume of case-law documents characterised by formalised language, lengthy sentence s

applicationsarxiv-cs-cl

TrianguLang: Geometry-Aware Semantic Consensus for Pose-Free 3D Localization

arXiv:2603.08096v3 Announce Type: replace Abstract: Localizing objects and parts from natural language in 3D space is essential for robotics, AR, and embodied AI, yet existing methods face a trade-off

When More Words Say Less: Decoupling Length and Specificity in Image Description Evaluation

arXiv:2601.04609v2 Announce Type: replace Abstract: Vision-language models (VLMs) are increasingly used to make visual content accessible via text-based descriptions. In current systems, however, desc

A PennyLane-Centric Dataset to Enhance LLM-based Quantum Code Generation using RAG

model-releasesarxiv-cs-ai

arXiv:2503.02497v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) offer powerful capabilities in code generation, natural language understanding, and domain-specific reasoning. Th

20 Apr 2026

AdaVFM: Adaptive Vision Foundation Models for Edge Intelligence via LLM-Guided Execution

arXiv:2604.15622v1 Announce Type: new Abstract: Language-aligned vision foundation models (VFMs) enable versatile visual understanding for always-on contextual AI, but their deployment on edge devices

20 Apr 2026

ChemGraph-XANES: An Agentic Framework for XANES Simulation and Analysis