Search: “retrieval”

Theory-Guided Deception Detection: A RAG-Based Artificial Intelligence Exploration

arXiv:2608.08881v1 Announce Type: new Abstract: The current work developed seven Retrieval-Augmented Generation (RAG) models based on leading deception theories and compared how deception judgments we

11 Aug 2026

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Calibrating WEAT Against Anisotropy: ZCA Whitening as a Geometric Pre-Processing Step for Embedding Association Tests

DGX agent

arXiv:2608.06908v1 Announce Type: cross Abstract: We propose Zero-phase Component Analysis (ZCA) whitening as a geometric pre-processing step for the Word Embedding Association Test (WEAT). WEAT is a

safetyarxiv-cs-ai

10 Aug 2026

Dual-Space Modality Consistency Learning for Universal Cross-Modal Re-Identification

arXiv:2608.06943v1 Announce Type: new Abstract: Cross-modal Re-Identification (ReID) aims to retrieve the same identity across heterogeneous imaging modalities and has been widely studied in visible-i

safetyarxiv-cs-cv

ED-CSP: Crystal Structure Prediction from Electron Diffraction

arXiv:2608.06448v1 Announce Type: cross Abstract: Recovering a periodic 3D crystal structure from sparse, unindexed electron diffraction (ED) observations is a challenging generative inverse problem.

HNR-DAC: Hard-Negative Reranking and Distribution-Aligned Classification for Scientific Claim Verification

arXiv:2608.07204v1 Announce Type: new Abstract: Scientific claim verification over a cited paper requires predicting the claim--paper relation and identifying the paragraphs that justify that predicti

Latent Fact-Checking: Detecting Misinformation through Activation Engineering

arXiv:2608.06417v1 Announce Type: cross Abstract: The proliferation of misinformation online has driven demand for scalable detection systems. While most existing approaches rely on surface-level ling

oldsymbol{lambda}-Orthogonality Regularization for Compatible Representation Learning

arXiv:2509.16664v2 Announce Type: cross Abstract: Retrieval systems rely on representations learned by increasingly powerful models. However, due to the high training cost and inconsistencies in learn

researcharxiv-cs-cv

Causal Episodic Memory for Feedback-Driven Agent Repair

arXiv:2608.05906v1 Announce Type: new Abstract: LLM agents that repair failures often discard successful corrections, forcing later episodes to rediscover similar solutions. We study whether finalized

CRINN: Contrastive Reinforcement Learning for Approximate Nearest Neighbor Search

arXiv:2508.02091v4 Announce Type: replace-cross Abstract: Approximate nearest-neighbor search (ANNS) algorithms have become increasingly critical for recent AI applications, particularly in retrieval-

Example-Guided Prompting for Document-Level Text Simplification

arXiv:2608.05447v1 Announce Type: new Abstract: Document-level text simplification requires large language models (LLMs) to rewrite complex documents while preserving meaning, readability, and discour

LLM Inference Under Bursty Workload Distribution: Modifying the WAIT Algorithm

model-releasesarxiv-cs-lg

arXiv:2608.06135v1 Announce Type: new Abstract: Large Language Models (LLMs) such as ChatGPT and Claude are widely used for information retrieval and problem-solving. Recent work has focused on improv

SCI-CLIP: Segment-Centric Inference with Reference Memory for Training-Free Open-Vocabulary Segmentation

arXiv:2608.05627v1 Announce Type: new Abstract: Training-free open-vocabulary segmentation remains limited by a missing inference abstraction. Frozen vision-language features are produced at patch lev

safetyarxiv-cs-cv

SkillZip: Contract-Preserving Graph Compression for Scalable Agent Skill Libraries

arXiv:2608.05604v1 Announce Type: cross Abstract: Large Language Models (LLMs) increasingly act as agents whose procedural knowledge is stored in reusable skill packages and loaded at inference time.

Universal Pathologies, Conditional Consequences: A Triple-Robustness Analysis of RAG for Multi-Hop Traceability

arXiv:2608.05153v1 Announce Type: cross Abstract: GraphRAG underperforms vector RAG on citation precision in many reports, but where and why have remained corpus-bound. We present a triple-robustness

A/B Agent: A Self-Evolving Agent for Strategy Iteration in Industrial A/B Testing

arXiv:2608.04625v1 Announce Type: new Abstract: Industrial recommendation strategy iteration heavily relies on large-scale A/B experimentation. Traditional tuning requires experts to repeatedly design

safetyarxiv-cs-ai

ABSeeker: Training Long-Horizon Search Agents via Answer-Backtracked Credit Assignment

arXiv:2608.05102v1 Announce Type: new Abstract: Long-horizon search agents must make multiple sequential actions (steps) to search, retrieve, verify, and integrate evidence to reach a final answer. Ho

Caching for the Future: Scrub Jay Episodic Memory Principles for Agent Memory Systems

arXiv:2608.04746v1 Announce Type: new Abstract: LLM agents that persist across sessions accumulate stored memories whose validity varies enormously by content type, yet existing memory architectures t

CARGO-VL: Counterfactual Arbitration with Risk-Constrained Group Optimization for Vision-Language Models

arXiv:2608.04509v1 Announce Type: new Abstract: Vision-language systems combine images with retrieved text, but these sources can disagree or jointly fail to support an answer. Reliable models must id

safetyarxiv-cs-ai

Combating Knowledge Corruption in Agent Systems: A Byzantine-Tolerant Secure Collaborative RAG Framework

arXiv:2608.04366v1 Announce Type: cross Abstract: While retrieval-augmented generation systems partially address the hallucination issues in large language models, it also introduces new vulnerabiliti

D^2F-ReAG: Dynamic Decomposition and Filtering for Multi-Hop Reasoning-Augmented Generation

arXiv:2608.04444v1 Announce Type: cross Abstract: Large language models (LLMs) often generate inaccurate answers due to their reliance on static internal knowledge. Retrieval-augmented generation (RAG

EdgeLM: Edge Demonstrations for Language Models' Table Understanding

arXiv:2608.04390v1 Announce Type: new Abstract: Large language models (LLMs) perform table-centric prediction through in-context learning, making demonstration selection critical to performance. Exist

Hierarchical Graph Memory for LLM Agents with Path-level Localization and Rewrite

arXiv:2608.05095v1 Announce Type: new Abstract: Agents for long term reasoning require a memory that can be efficiently and effectively updated over time, as new facts and external feedback continue t

Mamba with Hierarchical Memory: Solving Representation Bottleneck in Long Sequence Modeling

arXiv:2608.02347v2 Announce Type: replace Abstract: Recurrent linear attention models (RLAs) such as Mamba offer efficient linear-time sequence modeling as an alternative to Transformers, yet their fi

Neighborhood-Aware Dual Biomedical Entity Linking

arXiv:2608.04144v1 Announce Type: cross Abstract: Biomedical entity linking grounds mentions in clinical and scientific text to entities in a curated knowledge base (KB) with ontological structure, wh

Tutorials

The RAIL Principles for Neurosymbolic AI: Reasoning, Assurances, Interfacing and Learning

arXiv:2608.04285v1 Announce Type: new Abstract: Neurosymbolic AI systems that integrate machine learning and symbolic reasoning are rapidly gaining attention. They complement the data-intensive statis

tutorialsarxiv-cs-ai

When Absence Is Evidence: Evaluating Completeness-Sensitive Negative Reasoning in Large Language Models

arXiv:2608.04591v1 Announce Type: cross Abstract: Large language models (LLMs) are often asked whether something is absent from a record, list, or retrieved context. Yet non-observation licenses a neg

Distractor-Aware Truncation: Disentangling Context-Length Effects from Signal Loss in Long-Context LLM Benchmarks

arXiv:2608.03297v1 Announce Type: new Abstract: A standard claim in the literature on retrieval-augmented and memory-augmented language models is that shorter context is better when the relevant infor

HyperAgent: Planning and Acting over Tool-Schema Hypergraphs for Tool-Use LLM Agents

arXiv:2608.02650v1 Announce Type: new Abstract: Large language model (LLM) agents increasingly rely on external tools to complete complex real-world tasks. However, reliable tool-use planning remains

HyperFL: Query-Adaptive Representation Learning for Software Fault Localization

arXiv:2608.02967v1 Announce Type: cross Abstract: Software fault localization identifies the code locations responsible for reported issues and is a fundamental step toward automated debugging and pro

Material-Segmented Per-Pixel Emissivity Correction for Thermographic Anomaly Detection in Cultural Heritage Digital Twins

model-releasesarxiv-cs-cv

arXiv:2608.02964v1 Announce Type: new Abstract: Quantitative longwave thermography of heritage surfaces is limited by the global-constant emissivity assumption in inverse-Planck temperature retrieval;

PULSE: An Executable Contract Language for Spatiotemporal Knowledge Graph Engineering

arXiv:2608.02630v1 Announce Type: new Abstract: Knowledge graph engineering often distributes accepted state, observations, constraints, processes, and hypothetical scenarios across artifacts whose co

safetyarxiv-cs-ai

TARL: Transaction-Aware Reliable Ledgers for Executable Memory Management in Long-Term Agents

arXiv:2608.03699v1 Announce Type: new Abstract: Persistent memory helps long-term agents retain knowledge, yet a single update error can repeatedly distort future retrieval and reasoning. Most existin

TimeRLM: Recursive Language Models Enable Precise Anomaly Localization in Long-Context Time-Series

model-releasesarxiv-cs-lg

arXiv:2608.03391v1 Announce Type: new Abstract: Precise anomaly localization over long-context time series is a crucial task in monitoring applications across clinical care, industrial operations, fin

VIBE: Vector Index Benchmark for Embeddings

model-releasesarxiv-cs-lg

arXiv:2505.17810v2 Announce Type: replace Abstract: Approximate nearest neighbor (ANN) search is a performance-critical component of many machine learning pipelines, and rigorous benchmarking is essen

When Attention Goes Blind: Numerical Failure in ALiBi Positional Encodings

arXiv:2608.03994v1 Announce Type: new Abstract: We identify a previously overlooked failure mode of ALiBi positional encoding: its linear bias scaling underflows floating-point precision, which zeroes

AgentMemBench: A Systematic Benchmark for Evaluating Long-Term Memory Management Strategies in Conversational AI Agents

arXiv:2608.00009v1 Announce Type: new Abstract: Long-term memory remains a critical bottleneck for conversational AI agents, whose finite context windows cannot support coherent recall across thousand

DART: Decoded Attention over Recurrent States for Efficient Long-Context Sequence Modeling

arXiv:2608.02032v1 Announce Type: new Abstract: Modern language models are built primarily from Transformers, recurrent models, and their hybrid architectures. Transformers rely on token-level attenti

researcharxiv-cs-lg

GeoArbiter: Verifiability-Guided Grounding for Remote-Sensing Multimodal LLMs

arXiv:2608.00877v1 Announce Type: new Abstract: Remote-sensing multimodal large language models (MLLMs) often assert facts that imagery cannot establish, such as a facility's identity or function. Coo

safetyarxiv-cs-lg

Applications

MUSS: Multilevel Subset Selection for Relevance and Diversity

arXiv:2503.11126v4 Announce Type: replace Abstract: The problem of relevant and diverse subset selection has a wide range of applications, including recommender systems and retrieval-augmented generat

applicationsarxiv-cs-lg

On the Wings of Imagination: Conflicting Script-based Multi-role Framework for Humor Caption Generation

arXiv:2602.06423v2 Announce Type: replace Abstract: Humor is a commonly used and intricate human language in daily life. Humor generation, especially in multi-modal scenarios, is a challenging task fo

One Query, Many Scales: Sparse Mixture-of-Experts for Efficient Hierarchical Cross-View Geo-Localization

model-releasesarxiv-cs-cv

arXiv:2608.01060v1 Announce Type: new Abstract: Cross-view geo-localization (CVGL) retrieves geo-tagged satellite imagery for a ground-view query. Most systems exhaustively search a flat, fixed-resolu

Local Ai

PatchAlign3D: Local Feature Alignment for Dense 3D Shape Understanding

arXiv:2601.02457v2 Announce Type: replace Abstract: Current foundation models for 3D shapes excel at global tasks (retrieval, classification) but transfer poorly to local part-level reasoning. Recent

local-aiarxiv-cs-cv

RadPRISM: Schema-stratified radiology-report supervision for concept-disentangled image representations and visual grounding

arXiv:2608.00147v1 Announce Type: new Abstract: Vision-language pretraining learns rich medical image representations from radiology reports, but previous model variants commonly operate within a sing

safetyarxiv-cs-cv

SafeBuild-Bench: A Temporal-Robust Construction Safety Benchmark with Graph-Enhanced Data Mining

model-releasesarxiv-cs-cv

arXiv:2608.00068v1 Announce Type: new Abstract: Construction-safety models must handle concrete deployment risks, such as a worker standing near a scaffold edge without guardrails, rather than only re

SERL-SQL: Selective Hindsight Distillation for Text-to-SQL Reinforcement Agentic Learning

arXiv:2608.00485v1 Announce Type: new Abstract: Recent Text-to-SQL systems increasingly rely on multi-turn interaction, execution feedback, and reinforcement learning. However, most existing methods u

Local Ai

StyleForge: Indoor Furniture Styling by Counterfactual Reasoning in a Hypergraph Field

arXiv:2608.01954v1 Announce Type: new Abstract: Fixed-layout indoor furniture styling requires selecting assets that form a coherent room without changing the prescribed furniture categories, position

local-aiarxiv-cs-cv

The Holistic Storage of Verb+Up Phrases in Text-based and Audio-based Language Models

arXiv:2606.13993v2 Announce Type: replace Abstract: A crucial aspect of linguistic capability is the ability to trade off between stored representations and abstract knowledge: one must retrieve learn

ELISA: An Interpretable Hybrid Generative AI Agent for Expression-Grounded Discovery in Single-Cell Genomics

arXiv:2603.11872v3 Announce Type: replace-cross Abstract: Translating single-cell RNA sequencing (scRNA-seq) data into mechanistic biological hypotheses remains a critical bottleneck, as agentic AI sy