Search: “retrieval”

From Extraction to Governed Memory: Multi-Agent Knowledge Graph Construction with Domain-Expert Review

arXiv:2608.28642v1 Announce Type: new Abstract: Knowledge graphs used by agentic systems are often treated as flat stores of extracted triples, with little record of who owns a fact, why it was admitt

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InternReviewer & InternAdvocate: Objective Reward and Evaluation for Agentic Reinforcement Learning in Peer Review and Rebuttal

DGX agent

arXiv:2608.28612v1 Announce Type: new Abstract: Generating professional scholarly content, such as peer reviews and rebuttals, requires an intricate synergy between domain reasoning and factual ground

safetyarxiv-cs-ai

1 Sept 2026

Kathleen Remembers: Length-Invariant One-Shot Recall Without Attention

arXiv:2608.30376v1 Announce Type: new Abstract: Recurrent, attention-free sequence models share a structural weakness: a fading state cannot perform exact recall of something seen once, far in the pas

MIND: Unified Inquiry and Diagnosis RL with Criteria Grounded Clinical Supports for Psychiatric Consultation

arXiv:2603.03677v2 Announce Type: replace-cross Abstract: Psychiatric consultation requires agents to elicit discriminative evidence, map uncertain narratives to diagnostic criteria, and decide when e

Overreliance on AI in Information-seeking from Video Content

arXiv:2603.19843v2 Announce Type: replace-cross Abstract: The ubiquity of multimedia content is reshaping online information spaces, particularly in social media environments. At the same time, search

safetyarxiv-cs-cl

Parametric Multimodal User Memory: Storing What Captions Cannot Carry

arXiv:2608.28609v1 Announce Type: cross Abstract: A personalized agent needs a user memory: a persistent model of who its user is. Today it is almost always text -- transcripts and captions retrieved

S3C-LLM: Skill-Code Guided Agentic Language Models for Spectrum-to-Structure Elucidation

arXiv:2608.30910v1 Announce Type: cross Abstract: Spectroscopic structure elucidation is central to molecular analysis, but recent Large Language Model (LLM)-based methods mostly formulate it as direc

agentsarxiv-cs-cl

UTILMEM: Benchmarking Evidence Utilization in Long-Term Conversational Memory

arXiv:2608.30508v1 Announce Type: new Abstract: Long-term memory is increasingly important for conversational agents, yet existing benchmarks primarily measure memory through pointwise factual recall:

WeAgent-MMSearch: Native Text-Vision Interaction for Multimodal Search Agents

arXiv:2608.28062v2 Announce Type: replace Abstract: Multimodal search agents extend parametric knowledge with newly emerging and long-tail evidence from the open web. Yet many existing agentic search

Local Ai

When Errors Become Memories: Causal Pathway Tracing in Multi-Turn Memory-Augmented LLMs

arXiv:2608.30198v1 Announce Type: new Abstract: Long-term memory enables large language models (LLMs) to preserve and reuse information across interactions, but it can also turn localized errors into

local-aiarxiv-cs-cl

Accelerating LLM Inference via Vector Index Based Output Embeddings

arXiv:2608.27460v1 Announce Type: new Abstract: Large output embedding matrices create a significant memory bandwidth bottleneck during autoregressive decoding, especially for compact LLMs with large

31 Aug 2026

How Far Can 5,500 Hours of Driving Take You? A Scaling Law Analysis of Video Diffusion Models

model-releasesarxiv-cs-cv

arXiv:2608.28404v1 Announce Type: new Abstract: Video generation for autonomous driving cannot follow the web-scale route: driving data is expensive to collect, bound by privacy requirements, and cann

31 Aug 2026

Interesting paper from Tencent. Tencent trains an agent to manage its own working context, and assigns credit at the level of individual con…

Interesting paper from Tencent. Tencent trains an agent to manage its own working context, and assigns credit at the level of individual context edits. Long-horizon tasks force a model to retrieve, in

agentsdair-ai--x

31 Aug 2026

CIFQA: A Deterministic Tool-Grounded Multi-Agent LLM Framework for Financial Query Answering

arXiv:2608.26114v1 Announce Type: new Abstract: Calculation-intensive financial question answering requires exact reasoning over structured rates, temporal conditions, numerical formulas, and rule-bas

CorporateBench: Large-Scale Q&A Benchmarking with Temporal Knowledge Bases

arXiv:2608.27391v1 Announce Type: new Abstract: LLMs are increasingly able to answer complex questions about enterprise-scale document collections. But evaluation is hard: companies don't want to shar

Decoupled I/O-Dominant Pipelines for Large-Scale Whole-Slide Image Embedding Extraction

arXiv:2608.27278v1 Announce Type: cross Abstract: Whole-slide images (WSIs) are central to computational pathology but are prohibitively large, making patch-based processing the practical unit for fou

researcharxiv-cs-cv

ElementCheck: Complexity-Aware Long-Form Text Factuality Evaluation via Sentence Elements

arXiv:2608.26118v1 Announce Type: new Abstract: Existing long-form factuality evaluation relies on the decompose-retrieve-verify pipeline. However, the pipeline suffers from noise from claim decomposi

ITL: Interpretable Document Alignment with Structured Reference Frameworks

arXiv:2608.27031v1 Announce Type: new Abstract: Measuring alignment between documents and structured reference frameworks requires identifying conceptual evidence distributed throughout the text and r

safetyarxiv-cs-cl

LLMs for Academic Workflows: An Evaluation of Literature Reviews Generated with Short and Long Context Windows of LLMs

arXiv:2608.26145v1 Announce Type: new Abstract: Our research focuses on evaluating literature reviews generated in short and long context settings of large language models (LLMs) to investigate the im

Omni-Interactive Universal Embedder

arXiv:2608.27044v1 Announce Type: new Abstract: Multimodal representation learning has been shifting from traditional two-tower architectures to large language model (LLM)-based embedders due to their

RedEvoAgent: Automatic Red-Teaming Agent with Experience-Driven Skill Evolution

arXiv:2608.27439v1 Announce Type: cross Abstract: LLM-based agents are increasingly deployed in product-level execution harnesses, where jailbreaks can trigger harmful tool use and persistent state ch

safetyarxiv-cs-ai

The Thousand-Graph Hypothesis: A Testable Hypothesis of Task-Conditioned Relation Materialization in Repository-Level Code Reasoning

arXiv:2608.26602v1 Announce Type: cross Abstract: Large software repositories are often beyond model context limits. Training repository knowledge into models is costly and quickly stale, while local

Towards Expert Financial QA via Self-Improving RAG

arXiv:2608.26706v1 Announce Type: new Abstract: Expert-level financial question answering requires both grounded verification to catch numeric hallucinations and audit trails for regulatory compliance

agentsarxiv-cs-cl

CAFE: Self-Improving Search Agents Need Co-Evolving Feedback

arXiv:2608.24794v1 Announce Type: new Abstract: Outcome-supervised search agents learn when and how to retrieve evidence, but terminal rewards neither localize intermediate errors nor redirect an ongo

Evidence Blindness in Direct Corpus Interaction: Persistent Navigation with AtlasNav

arXiv:2608.24764v1 Announce Type: new Abstract: Large language model agents are moving beyond conventional retrieval-augmented generation toward direct interaction with external corpora. Direct Corpus

Experiment with Qwen3.8-Flash-Next on NVIDIA GB300 NVL72 for Agentic Coding

model-releasesnvidia-developer

Qwen3.8‑Flash‑Next is a multimodal mixture‑of‑experts model with 125 B parameters that employs Gated DeltaNet (compressing historic context) and Qwen Sparse Attention (exact retrieval over full contex

Gated Activation Steering for Reducing Sycophancy & Hallucination in Medical Question Answering

arXiv:2608.23666v1 Announce Type: new Abstract: Sycophancy and hallucination are persistent failure modes of Large Language Models (LLMs) across domains. However, it becomes particularly consequential

Introducing the MLPerf End-to-End RAG Inference Benchmark

Benchmarking Retrieval-Augmented Generation End to End — from Building the Vector Database to Serving an Iterative, Multi-Hop Question-Answering Inference Pipeline The post Introducing the MLPerf End-

model-releasesmlcommons

MolEmb: Multimodal Large Language Models Can Be Strong Molecular Embedding Models

arXiv:2608.23646v1 Announce Type: new Abstract: Molecular embedding models can serve as foundational infrastructure for computational chemistry and drug discovery, where reusable vector representation

PRQ-KMeans: Projection Residual Quantization for Semantic ID Tokenization

arXiv:2608.24207v1 Announce Type: new Abstract: Semantic identifiers (SIDs) represent entities as hierarchical token sequences for generative retrieval and recommendation. Residual-quantization tokeni

researcharxiv-cs-lg

VideoHarness-RSI: Recursive Harness Self-Improvement for Long-Video Understanding with Frozen Vision-Language Models

arXiv:2608.24302v1 Announce Type: new Abstract: Long-video understanding depends critically on how a limited model context is constructed from a much longer video. Existing approaches improve this pro

WeMM-Embedding: WeChat Multi-Modal Embedding Technical Report

model-releasesarxiv-cs-cv

arXiv:2608.24053v1 Announce Type: new Abstract: Universal multimodal embeddings are becoming a core component of modern AI systems, enabling heterogeneous content to be represented in a shared space f

Aligning Biomedical Texts and Knowledge Graphs: A Systematic Comparison of Lightweight Alignment Strategies

arXiv:2608.23214v1 Announce Type: new Abstract: Biomedical knowledge exists in two complementary but distinct forms: unstructured scientific literature and structured knowledge graphs (KGs). Aligning

safetyarxiv-cs-cl

Boosting Knowledge-based Visual Question Answering with Structured Context Reasoning

arXiv:2608.21431v1 Announce Type: new Abstract: Knowledge-based Visual Question Answering aims to answer questions about an image by integrating external knowledge with visual and textual information.

researcharxiv-cs-cv

Compositional Chain-of-Relations for Faithful Knowledge Graph Question Answering with Large Language Models

arXiv:2608.22762v1 Announce Type: new Abstract: Knowledge graph question answering (KGQA) is a key task for evaluating KG-augmented Large Language Models (LLMs), and complex KGQA that requires multi-h

Hardware

CST: Collaborative Selective Transmission for Communication-Efficient Multimodal Edge Inference

arXiv:2608.22115v1 Announce Type: new Abstract: Collaborative multimodal inference improves edge perception by combining observations from distributed sensing devices, but transmitting high-dimensiona

hardwarearxiv-cs-lg

Dissecting Neuro-Symbolic Quality Assurance for Synthetic Oncology Data Generation

arXiv:2608.22085v1 Announce Type: new Abstract: Synthetic clinical data generation with large language models addresses the scarcity that limits cancer staging research, but oncology hallucinations ar

researcharxiv-cs-ai

EDGE: Experience-Distillation for Guided Exploration in Agentic Reinforcement Learning

arXiv:2608.21946v1 Announce Type: cross Abstract: Reinforcement learning with outcome-based objectives such as GRPO enables LLM-based agents to solve complex, long-horizon tasks, yet the reusable expl

safetyarxiv-cs-ai

Iteration Without Elaboration: A Simple ReAct Architecture Suffices for Text-to-SQL Generation

arXiv:2608.22651v1 Announce Type: new Abstract: Modern text-to-SQL systems have become increasingly elaborate, relying on schema-linking modules, retrieval-augmented prompting, candidate generation, a

researcharxiv-cs-cl

Model-Free Adaptive Parameter Tuning for Efficient Multi-Robot Warehouse Operations

model-releasesarxiv-cs-ro

arXiv:2608.21533v1 Announce Type: new Abstract: Robotic Fulfillment Centers (FCs) store inventory on shelves (pods) arranged in dense blocks. Retrieving a target pod that is buried deep in a block req

Local Ai

Role-Specialized Mixture-of-Agents with Open-Weight LLMs for Clinical Prediction

arXiv:2608.22176v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly applied to clinical prediction tasks such as in-hospital mortality and readmission from electronic health

local-aiarxiv-cs-ai

Applications

The Laws of Context Allocation: Causal Measurement and Closed-Loop Orchestration in Generative Search

arXiv:2608.23252v1 Announce Type: cross Abstract: As Retrieval-Augmented Generation (RAG) shifts toward diverse portfolio generation, it is stymied by two critical bottlenecks: flawed measurement of e

applicationsarxiv-cs-cl

Thinking Beyond Videos: Unifying Video Reasoning and Deep Research for Open-World Video Agents

arXiv:2608.23329v1 Announce Type: cross Abstract: Open-world video understanding often requires a model to locate sparse visual evidence and acquire external knowledge that is absent from the video an

Training a Knowledge Base: Supervised Structure Learning for Agent-Curated Document Stores

arXiv:2608.21829v1 Announce Type: cross Abstract: Retrieval-augmented generation treats the document store as a frozen input, and the systems that instead let an agent curate one never measure what cu

Deep Learning Models Also Recall Features

arXiv:2608.20970v1 Announce Type: new Abstract: Recent work in mechanistic interpretability has studied how large language models recall facts stored in their weights. This paper argues that factual r

researcharxiv-cs-ai

Difficulty-Aware Semantic-ID Optimization for Generative Recommendation

arXiv:2608.20611v1 Announce Type: new Abstract: Semantic-ID-based generative recommendation casts retrieval and ranking as autoregressive generation over hierarchical item identifiers. A common recipe

safetyarxiv-cs-ai

Empowering autonomous agents with advanced security governance

model-releasesgoogle-cloud-ai

AI agents are the ultimate insiders. We grant them permission to read emails, query databases, and trigger API calls. They don’t just retrieve information, they take action. Agents offer incredible po

Applications

From a Static Multi-Level Small Semantic Codebook to a Dynamic Single-Level Large Semantic Codebook for Generative Recommendation

arXiv:2608.21012v1 Announce Type: cross Abstract: Generative recommendation represents each item with a sequence of discrete Semantic IDs (SIDs) and predicts the sequence to retrieve the next item. Ty

applicationsarxiv-cs-lg