Search: “retrieval”

Graphs of Research: Citation Evolution Graphs as Supervision for Research Idea Generation

arXiv:2605.14790v1 Announce Type: cross Abstract: Research idea generation is the innovation-driving step of automated scientific research. Recently, large language models (LLMs) have shown potential

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GroupMemBench: Benchmarking LLM Agent Memory in Multi-Party Conversations

DGX agent

arXiv:2605.14498v1 Announce Type: new Abstract: Large Language Model (LLM) agents increasingly serve as personal assistants and workplace collaborators, where their utility depends on memory systems t

model-releasesarxiv-cs-cl

15 May 2026

Herculean: An Agentic Benchmark for Financial Intelligence

arXiv:2605.14355v1 Announce Type: new Abstract: As AI agents improve, the central question is no longer whether they can solve isolated well-defined financial tasks, but whether they can reliably carr

Hidden State Poisoning Attacks against Mamba-based Language Models

arXiv:2601.01972v4 Announce Type: cross Abstract: State space models (SSMs) like Mamba offer efficient alternatives to Transformer-based language models, with linear time complexity. Yet, their advers

KGPFN: Unlocking the Potential of Knowledge Graph Foundation Model via In-Context Learning

arXiv:2605.14907v1 Announce Type: new Abstract: Knowledge graph (KG) foundation models aim to generalize across graphs with unseen entities and relations by learning transferable relational structure.

Known By Their Actions: Fingerprinting LLM Browser Agents via UI Traces

arXiv:2605.14786v1 Announce Type: cross Abstract: As LLM-based agents increasingly browse the web on users' behalf, a natural question arises: can websites passively identify which underlying model po

agentsarxiv-cs-ai

LLMs Should Express Uncertainty Explicitly

arXiv:2604.05306v2 Announce Type: replace-cross Abstract: Large language models (LLMs) often produce confident yet incorrect answers, which can lead to risky failures in real-world applications. We st

MemEye: A Visual-Centric Evaluation Framework for Multimodal Agent Memory

arXiv:2605.15128v1 Announce Type: cross Abstract: Long-term agent memory is increasingly multimodal, yet existing evaluations rarely test whether agents preserve the visual evidence needed for later r

MemLens: Benchmarking Multimodal Long-Term Memory in Large Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2605.14906v1 Announce Type: new Abstract: Memory is essential for large vision-language models (LVLMs) to handle long, multimodal interactions, with two method directions providing this capabili

MemLineage: Lineage-Guided Enforcement for LLM Agent Memory

arXiv:2605.14421v1 Announce Type: cross Abstract: We introduce MemLineage, a defense for LLM agent memory that attaches both cryptographic provenance and LLM-mediated derivation lineage to every entry

agentsarxiv-cs-ai

Mini-JEPA Foundation Model Fleet Enables Agentic Hydrologic Intelligence

arXiv:2605.14120v1 Announce Type: cross Abstract: Geospatial foundation models compress multispectral observations into dense embeddings increasingly used in natural-language environmental reasoning s

Proactive Memory for Ad-Hoc Recall over Streaming Dialogues

arXiv:2603.04885v2 Announce Type: replace Abstract: Real-world dialogue usually unfolds as an infinite stream. It thus requires bounded-state memory mechanisms to operate within an infinite horizon. H

Reinforcement Learning for Tool-Calling Agents in Fast Healthcare Interoperability Resources (FHIR)

arXiv:2605.14126v1 Announce Type: cross Abstract: Fast Healthcare Interoperability Resources (FHIR) is the dominant standard for interoperable exchange of healthcare data. In FHIR, electronic health r

Remember Your Trace: Memory-Guided Long-Horizon Agentic Framework for Consistent and Hierarchical Repository-Level Code Documentation

arXiv:2605.14563v1 Announce Type: cross Abstract: Automated code documentation is essential for modern software development, providing the contextual grounding that both human developers and coding ag

agentsarxiv-cs-cl

Residual Stream Duality in Modern Transformer Architectures

arXiv:2603.16039v2 Announce Type: replace-cross Abstract: Recent work has made clear that the residual pathway is not mere optimization plumbing; it is part of the model's representational machinery.

Rethinking Molecular OOD Generalization via Target-Aware Source Selection

arXiv:2605.13932v1 Announce Type: new Abstract: Robust prediction of molecular properties under extreme out-of-distribution (OOD) scenarios is a pivotal bottleneck in AI-driven drug discovery. Current

RQ-MoE: Residual Quantization via Mixture of Experts for Efficient Input-Dependent Vector Compression

arXiv:2605.14359v1 Announce Type: cross Abstract: Vector quantization is a fundamental tool for compressing high-dimensional embeddings, yet existing multi-codebook methods rely on static codebooks th

SciPaths: Forecasting Pathways to Scientific Discovery

arXiv:2605.14600v1 Announce Type: new Abstract: Scientific progress depends on sequences of enabling contributions, yet existing AI4Science benchmarks largely focus on citation prediction, literature

Self-Distilled Agentic Reinforcement Learning

arXiv:2605.15155v1 Announce Type: cross Abstract: Reinforcement learning (RL) has emerged as a central paradigm for post-training LLM agents, yet its trajectory-level reward signal provides only coars

SemaTune: Semantic-Aware Online OS Tuning with Large Language Models

arXiv:2605.15026v1 Announce Type: cross Abstract: Online OS tuning can improve long-running services, but existing controllers are poorly matched to live hosts. They treat scheduler, power, memory, an

Towards Continuous Sign Language Conversation from Isolated Signs

arXiv:2605.14705v1 Announce Type: new Abstract: Sign language is the primary language for many Deaf and Hard-of-Hearing (DHH) signers, yet most conversational AI systems still mediate interaction thro

safetyarxiv-cs-cv

Action Emergence from Streaming Intent

model-releasesarxiv-cs-cv

arXiv:2605.12622v1 Announce Type: cross Abstract: We formalize action emergence as a target capability for end-to-end autonomous driving: the ability to generate physically feasible, semantically appr

Aligning Forest and Trees in Images & Long Captions for Visually Grounded Understanding

arXiv:2602.02977v2 Announce Type: replace-cross Abstract: Vision-language models such as CLIP often struggle to faithfully understand long, detail-rich captions, relying on dominant scene cues while o

An Agentic AI Framework with Large Language Models and Chain-of-Thought for UAV-Assisted Logistics Scheduling with Mobile Edge Computing

arXiv:2605.13221v1 Announce Type: new Abstract: In cloud manufacturing, unmanned aerial vehicles (UAVs) can support both product collection and mobile edge computing (MEC). This joint operation forms

An Agentic LLM-Based Framework for Population-Scale Mental Health Screening

arXiv:2605.13046v1 Announce Type: new Abstract: Mental health disorders affect millions worldwide, and healthcare systems are increasingly overwhelmed by the volume of clinical data generated from ele

agentsarxiv-cs-ai

BoostTaxo: Zero-Shot Taxonomy Induction via Boosting-Style Agentic Reasoning and Constraint-Aware Calibration

arXiv:2605.12520v1 Announce Type: cross Abstract: Taxonomy induction is crucial for organizing concepts into explicit and interpretable semantic hierarchies. While existing methods have achieved promi

CANTANTE: Optimizing Agentic Systems via Contrastive Credit Attribution

arXiv:2605.13295v1 Announce Type: cross Abstract: LLM-based multi-agent systems have demonstrated strong performance across complex real-world tasks, such as software engineering, predictive modeling,

Continual Fine-Tuning of Large Language Models via Program Memory

arXiv:2605.13162v1 Announce Type: new Abstract: Parameter-Efficient Fine-Tuning (PEFT), particularly Low-Rank Adaptation (LoRA), has become a standard approach for adapting Large Language Models (LLMs

Exploring Multimodal LMMs for Online Episodic Memory Question Answering on the Edge

model-releasesarxiv-cs-cv

arXiv:2602.22455v2 Announce Type: replace Abstract: We investigate the feasibility of using Multimodal Large Language Models (MLLMs) for real-time online episodic memory question answering. While clou

FIKA-Bench: From Fine-grained Recognition to Fine-Grained Knowledge Acquisition

arXiv:2605.13193v1 Announce Type: new Abstract: Fine-grained recognition in everyday life is often not a closed-book classification problem: when encountering unfamiliar objects, humans actively searc

agentsarxiv-cs-cv

Guidestar-Free Adaptive Optics with Asymmetric Apertures

arXiv:2602.07029v3 Announce Type: replace-cross Abstract: This work introduces the first closed-loop adaptive optics (AO) system capable of optically correcting aberrations in real-time without a guid

researcharxiv-cs-cv

Is a Picture Worth a Thousand Words? Adaptive Multimodal Fact-Checking with Visual Evidence Necessity

arXiv:2604.04692v2 Announce Type: replace-cross Abstract: Automated fact-checking is a crucial task that supports a responsible information ecosystem. While recent research has progressed from text-on

Lifelong Learning in Vision-Language Models: Enhanced EWC with Cross-Modal Knowledge Retention

model-releasesarxiv-cs-ro

arXiv:2605.12789v1 Announce Type: new Abstract: Large language-vision models (LVLMs) such as CLIP, Flamingo, and BLIP have revolutionized AI by enabling understanding across textual and visual modalit

Locale-Conditioned Few-Shot Prompting Mitigates Demonstration Regurgitation in On-Device PII Substitution with Small Language Models

arXiv:2605.13538v1 Announce Type: cross Abstract: Personally Identifiable Information (PII) redaction usually replaces detected entities with placeholder tokens such as [PERSON], destroying the downst

McCast: Memory-Guided Latent Drift Correction for Long-Horizon Precipitation Nowcasting

arXiv:2605.13197v1 Announce Type: cross Abstract: Existing precipitation nowcasting methods typically adopt an autoregressive formulation, where future states are predicted from previous outputs. Howe

Phasor Memory Networks: Stable Backpropagation Through Time for Scalable Explicit Memory

arXiv:2605.13370v1 Announce Type: new Abstract: For over a decade, explicit memory architectures like the Neural Turing Machine have remained theoretically appealing yet practically intractable for la

PROMETHEUS: Automating Deep Causal Research Integrating Text, Data and Models

arXiv:2605.12835v1 Announce Type: new Abstract: Large language models can extract local causal claims from text, but those claims become more useful when organized as persistent, navigable world model

QLAM: A Quantum Long-Attention Memory Approach to Long-Sequence Token Modeling

arXiv:2605.13833v1 Announce Type: cross Abstract: Modeling long-range dependencies in sequential data remains a central challenge in machine learning. Transformers address this challenge through atten

researcharxiv-cs-cv

Quantitative Certification of Agentic Tool Selection

arXiv:2510.03992v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly deployed in agentic systems, where a fundamental task is mapping user intents to relevant extern

ReTool-Video: Recursive Tool-Using Video Agents with Meta-Augmented Tool Grounding

arXiv:2605.13228v1 Announce Type: cross Abstract: Video understanding requires active evidence seeking, motivating tool-augmented video agents for temporal reasoning, cross-modal understanding, and co

RTLC -- Research, Teach-to-Learn, Critique: A three-stage prompting paradigm inspired by the Feynman Learning Technique that lifts LLM-as-judge accuracy on JudgeBench with no fine-tuning

arXiv:2605.13695v1 Announce Type: cross Abstract: LLM-as-a-judge is now the default measurement instrument for open-ended generation, but on the public JudgeBench benchmark even strong instruction-tun

ScioMind: Cognitively Grounded Multi-Agent Social Simulation with Anchoring-Based Belief Dynamics and Dynamic Profiles

arXiv:2605.13725v1 Announce Type: new Abstract: Large language model (LLM)-based multi-agent simulation offers a powerful testbed for studying social opinion dynamics. Yet current approaches often ado

SMA: Submodular Modality Aligner For Data Efficient Multimodal Learning

arXiv:2605.12872v1 Announce Type: new Abstract: Despite the recent success of Multimodal Foundation Models (FMs), their reliance on massive paired datasets limits their applicability in low-data and r

VideoSEAL: Mitigating Evidence Misalignment in Agentic Long Video Understanding by Decoupling Answer Authority

arXiv:2605.12571v1 Announce Type: cross Abstract: Long video question answering requires locating sparse, time-scattered visual evidence within highly redundant content. Although current MLLMs perform

A Theoretical Analysis of Why Masked Diffusion Models Mitigate the Reversal Curse

arXiv:2602.02133v2 Announce Type: replace-cross Abstract: Autoregressive language models (ARMs) suffer from the reversal curse: after learning ''A is B,'' they often fail on the reverse query ''B is A

AgentDisCo: Towards Disentanglement and Collaboration in Open-ended Deep Research Agents

arXiv:2605.11732v1 Announce Type: cross Abstract: In this paper, we present AgentDisCo, a novel Disentangled and Collaborative agentic architecture that formulates deep research as an adversarial opti

An Empirical Study of Automating Agent Evaluation

arXiv:2605.11378v1 Announce Type: new Abstract: Agent evaluation requires assessing complex multi-step behaviors involving tool use and intermediate reasoning, making it costly and expertise-intensive

Tutorials

CausalCine: Real-Time Autoregressive Generation for Multi-Shot Video Narratives

arXiv:2605.12496v1 Announce Type: new Abstract: Autoregressive video generation aims at real-time, open-ended synthesis. Yet, cinematic storytelling is not merely the endless extension of a single sce

tutorialsarxiv-cs-cv