Search: “retrieval”

Closed Loop Dynamic Driving Data Mixture for Real-Synthetic Co-Training

arXiv:2605.21372v1 Announce Type: new Abstract: Data scaling is fundamental to modern deep learning, and grows increasingly critical as autonomous driving shifts to end-to-end learning. Real-world dri

agentsarxiv-cs-cv

21 May 2026

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Faster or Stronger: Towards Flexible Visual Place Recognition via Weighted Aggregation and Token Pruning

DGX agent

arXiv:2605.20551v1 Announce Type: new Abstract: Visual Place Recognition (VPR) aims to match a query image to reference images of the same place in a large-scale database. Recent state-of-the-art meth

researcharxiv-cs-cv

21 May 2026

Memory Grafting: Scaling Language Model Pre-training via Offline Conditional Memory

arXiv:2605.20948v1 Announce Type: new Abstract: Scaling conditional memory offers a promising way to increase language-model capacity, but existing methods such as Engram learn large memory tables fro

21 May 2026

USV: Towards Understanding the User-generated Short-form Videos

arXiv:2605.20838v1 Announce Type: new Abstract: Several large-scale video datasets have been published these years and have advanced the area of video understanding. However, the newly emerged user-ge

researcharxiv-cs-cv

21 May 2026

A Geometric Analysis of Small-sized Language Model Hallucinations

arXiv:2602.14778v3 Announce Type: replace-cross Abstract: Hallucinations -- plausible but factually incorrect responses -- pose a major challenge to the reliability of Large Language Models (LLMs), es

Accurate, Efficient, and Explainable Deep Learning Approaches for Environmental Science Problems

arXiv:2605.19366v1 Announce Type: new Abstract: Environmental science plays a pivotal role in safeguarding ecosystems, a domain driven by large-scale, heterogeneous data. In the big data era, artifici

researcharxiv-cs-lg

DualView: Adaptive Local-Global Fusion for Multi-Hop Document Reranking

arXiv:2605.18767v1 Announce Type: cross Abstract: Multi-hop question answering requires aggregating information from multiple documents, a critical capability for knowledge-intensive applications. A f

Governing Evolving Memory in LLM Agents: Risks, Mechanisms, and the Stability and Safety Governed Memory (SSGM) Framework

arXiv:2603.11768v2 Announce Type: replace Abstract: Long-term memory has emerged as a foundational component of autonomous Large Language Model (LLM) agents, enabling continuous adaptation, lifelong m

Harnessing Self-Supervised Features for Art Classification

arXiv:2605.18974v1 Announce Type: cross Abstract: Classifying artworks presents a significant challenge due to the complex interplay of fine-grained details and abstract features that condition the st

MSAlign: Aligning Molecule and Mass Spectra Foundation Models for Metabolite Identification

model-releasesarxiv-cs-lg

arXiv:2605.19752v1 Announce Type: new Abstract: Accurately identifying metabolites i.e. small molecules from mass spectrometry data remains a core challenge in metabolomics, with broad applications in

No Hard Negatives Required: Concept Centric Learning Leads to Compositionality without Degrading Zero-shot Capabilities of Contrastive Models

model-releasesarxiv-cs-cv

arXiv:2603.25722v2 Announce Type: replace Abstract: Contrastive vision-language (V&L) models remain a popular choice for various applications. However, several limitations have emerged, most notably t

Towards Camera-Robust 3D Localization: Equation-Anchored Tool-Use for MLLMs

model-releasesarxiv-cs-cv

arXiv:2605.19528v1 Announce Type: new Abstract: 3D localization in Multimodal Large Language Models (MLLMs), including 3D object detection and 3D visual grounding, is fundamentally limited by camera i

Automated Root-Cause Subclassification and No-Code Fix Generation for Invalid Bug Reports

arXiv:2605.17561v1 Announce Type: cross Abstract: Issues faced when using software are reported in the form of bug reports. However, many bug reports are invalid, meaning they do not require code chan

Local Ai

BLAgent: Agentic RAG for File-Level Bug Localization

arXiv:2605.17965v1 Announce Type: cross Abstract: Bug localization remains a key bottleneck in downstream software maintenance tasks, including root cause analysis, triage, and automated program repai

local-aiarxiv-cs-ai

CommitDistill: A Lightweight Knowledge-Centric Memory Layer for Software Repositories

arXiv:2605.18284v1 Announce Type: cross Abstract: Software repositories accumulate large amounts of unstructured knowledge in commit messages, pull-request discussions, and issue threads, but develope

Compress the Context, Keep the Commitments: A Formal Framework for Verifiable LLM Context Compression

arXiv:2605.17304v1 Announce Type: cross Abstract: LLM context is not just tokens; it is a set of commitments. Long-running conversations accumulate goals, constraints, decisions, preferences, tool res

safetyarxiv-cs-cl

Enhancing Metacognitive AI: Knowledge-Graph Population with Graph-Theoretic LLM Enrichment

arXiv:2605.16676v1 Announce Type: new Abstract: Metacognition-the ability to monitor one's own knowledge state, spot gaps, and autonomously fill them--remains largely absent from modern AI. Here, we p

EvoMemBench: Benchmarking Agent Memory from a Self-Evolving Perspective

arXiv:2605.18421v1 Announce Type: cross Abstract: Recent benchmarks for Large Language Model (LLM) agents mainly evaluate reasoning, planning, and execution. However, memory is also essential for agen

Geometry-Editable and Appearance-Preserving Object Compositon

arXiv:2505.20914v2 Announce Type: replace Abstract: General object composition (GOC) aims to seamlessly integrate a target object into a background scene with desired geometric properties, while simul

researcharxiv-cs-cv

Key-Gram: Extensible World Knowledge for Embodied Manipulation

arXiv:2605.18556v1 Announce Type: cross Abstract: Embodied control increasingly requires models to follow compositional language instructions while reasoning over dynamic visual states. However, curre

LongMINT: Evaluating Memory under Multi-Target Interference in Long-Horizon Agent Systems

arXiv:2605.18565v1 Announce Type: cross Abstract: Real-world agents operate over long and evolving horizons, where information is repeatedly updated and may interfere across memories, requiring accura

Local Ai

MementoGUI: Learning Agentic Multimodal Memory Control for Long-Horizon GUI Agents

arXiv:2605.18652v1 Announce Type: new Abstract: Recent GUI agents have made substantial progress in visual grounding and action prediction, yet they remain brittle in long-horizon tasks that require m

local-aiarxiv-cs-cv

Multi-Order Matching Network for Alignment-Free Depth Super-Resolution

arXiv:2511.16361v3 Announce Type: replace Abstract: Recent guided depth super-resolution methods are premised on the assumption of strict spatial alignment between depth and RGB, achieving high-qualit

safetyarxiv-cs-cv

PERMA: Benchmarking Personalized Memory Agents via Event-Driven Preference and Realistic Task Environments

arXiv:2603.23231v2 Announce Type: replace Abstract: Empowering large language models with long-term memory is crucial for building agents that adapt to users' evolving needs. Existing evaluations of t

Query-Conditioned Knowledge Alignment for Reliable Cross-System Medical Reasoning

arXiv:2605.18570v1 Announce Type: new Abstract: Cross-domain knowledge alignment is essential for integrating heterogeneous medical systems, yet existing approaches typically treat entity alignment as

Skills on the Fly: Test-Time Adaptive Skill Synthesis for LLM Agents

arXiv:2605.16986v1 Announce Type: cross Abstract: LLM agents benefit from reusable skills, yet test-time tasks often require guidance more specific than a static skill library can provide. We propose

A Cascaded Generative Approach for e-Commerce Recommendations

arXiv:2605.11118v2 Announce Type: replace Abstract: Personalized storefronts in large e-commerce marketplaces are often assembled from many independent components: static themes per page section ('pla

From Full and Partial Intraoral Scans to Crown Proposal: A Classification-Guided Restoration Assistance Pipeline

arXiv:2605.15241v1 Announce Type: cross Abstract: Single-unit crown restoration is among the most common procedures in clinical dentistry, with CAD/CAM workflows now designing crowns directly from int

safetyarxiv-cs-cv

Hidden in Memory: Sleeper Memory Poisoning in LLM Agents

arXiv:2605.15338v1 Announce Type: cross Abstract: Large language models are increasingly augmented with persistent memory, allowing assistants to store user-specific information across sessions for pe

ScreenSearch: Uncertainty-Aware OS Exploration

arXiv:2605.16024v1 Announce Type: new Abstract: Desktop GUI agents operate under partial observability: visually similar screens can correspond to different underlying workflow states, so locally plau

SKILL0: In-Context Agentic Reinforcement Learning for Skill Internalization

arXiv:2604.02268v2 Announce Type: replace Abstract: Agent skills, structured packages of procedural knowledge and executable resources that agents dynamically load at inference time, have become a rel

safetyarxiv-cs-lg

SMMBench: A Benchmark for Source-Distributed Multimodal Agent Memory

arXiv:2605.15710v1 Announce Type: new Abstract: Existing benchmarks for multimodal memory reasoning largely evaluate systems within pre-assembled contexts, but under-evaluate whether agents can use ev

TokenButler: Token Importance is Predictable

arXiv:2503.07518v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) rely on the Key-Value (KV) Cache to store token history, enabling efficient decoding of tokens. As the KV-Cache g

Chain-of-Procedure: Hierarchical Visual-Language Reasoning for Procedural QA

arXiv:2605.14928v1 Announce Type: new Abstract: Recent advances in vision-language models (VLMs) have achieved impressive results on standard image-text tasks, yet their potential for visual procedure

DUET: Dual-Paradigm Adaptive Expert Triage with Single-cell Inductive Prior for Spatial Transcriptomics Prediction

arXiv:2605.14104v1 Announce Type: new Abstract: Inferring spatially resolved gene expression from histology images offers a cost-effective complement to spatial transcriptomics (ST). However, existing

researcharxiv-cs-cv

Ergodic Imitation for Adaptive Exploration around Demonstrations

arXiv:2605.13996v1 Announce Type: new Abstract: In robotics, a common challenge in imitation learning is the mismatch between training and deployment conditions, caused, for example, by environmental

researcharxiv-cs-ro

Evidential Reasoning Advances Interpretable Real-World Disease Screening

arXiv:2605.15171v1 Announce Type: cross Abstract: Disease screening is critical for early detection and timely intervention in clinical practice. However, most current screening models for medical ima

Grounded Continuation: A Linear-Time Runtime Verifier for LLM Conversations

arXiv:2605.14175v1 Announce Type: new Abstract: In long conversations, an LLM can produce a next utterance that sounds plausible but rests on premises the conversation has already abandoned. Context-m

MeMo: Memory as a Model

arXiv:2605.15156v1 Announce Type: cross Abstract: Large language models (LLMs) achieve strong performance across a wide range of tasks, but remain frozen after pretraining until subsequent updates. Ma

ProtoMedAgent: Multimodal Clinical Interpretability via Privacy-Aware Agentic Workflows

arXiv:2605.14113v1 Announce Type: cross Abstract: While interpretable prototype networks offer compelling case-based reasoning for clinical diagnostics, their raw continuous outputs lack the semantic

RAPO++: Cross-Stage Prompt Optimization for Text-to-Video Generation via Data Alignment and Test-Time Scaling

arXiv:2510.20206v2 Announce Type: replace Abstract: Prompt design plays a crucial role in text-to-video (T2V) generation, yet user-provided prompts are often short, unstructured, and misaligned with t

safetyarxiv-cs-cv

Think When Needed: Adaptive Reasoning-Driven Multimodal Embeddings with a Dual-LoRA Architecture

arXiv:2605.14448v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have emerged as a powerful backbone for multimodal embeddings. Recent methods introduce chain-of-thought (CoT

A Multi-Agent Orchestration Framework for Venture Capital Due Diligence

arXiv:2605.13110v1 Announce Type: cross Abstract: We present a fully automated multi-agent framework for corporate due diligence and market analysis in venture capital. The system runs on an event-dri

Local Ai

AdaFocus: Adaptive Relevance-Diversity Sampling with Zero-Cache Look-back for Efficient Long Video Understanding

arXiv:2605.12954v1 Announce Type: cross Abstract: Long video understanding is heavily bottlenecked by a rigid one-shot paradigm: existing methods either densely encode videos at prohibitive memory and

local-aiarxiv-cs-ai

Automated Rubrics for Reliable Evaluation of Medical Dialogue Systems

arXiv:2601.15161v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly used for clinical decision support, where hallucinations and unsafe suggestions may pose direct

CROP: Expert-Aligned Image Cropping via Compositional Reasoning and Optimizing Preference

arXiv:2605.12545v1 Announce Type: cross Abstract: Aesthetic image cropping aims to enhance the aesthetic quality of an image by improving its composition through spatial cropping. Previous methods oft

GeoFlowVLM: Geometry-Aware Joint Uncertainty for Frozen Vision-Language Embedding

arXiv:2605.13352v1 Announce Type: new Abstract: Standard dual-encoder vision-language models that map images and text to deterministic points on a shared unit hypersphere through ell_2 normalization t

researcharxiv-cs-lg

Many-Shot CoT-ICL: Making In-Context Learning Truly Learn

arXiv:2605.13511v1 Announce Type: cross Abstract: In-context learning (ICL) adapts large language models (LLMs) to new tasks by conditioning on demonstrations in the prompt without parameter updates.