Search: “rag”

arXiv:2604.01348v2 Announce Type: replace Abstract: Test-time scaling has emerged as an effective way to improve language models on challenging reasoning tasks. However, most existing methods treat ea

tutorialsarxiv-cs-cl

REFLEX: Reference-Free Evaluation of Log Summarization via Large Language Model Judgment

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

DGX agent

arXiv:2511.07458v2 Announce Type: replace Abstract: Evaluating log summarization systems is challenging due to the lack of high-quality reference summaries and the limitations of existing metrics like

applicationsarxiv-cs-cl

21 Apr 2026

SIGMA: A Semantic-Grounded Instruction-Driven Generative Multi-Task Recommender at AliExpress

arXiv:2602.22913v2 Announce Type: replace-cross Abstract: With the rapid evolution of Large Language Models (LLMs), generative recommendation is gradually reshaping the paradigm of recommender systems

applicationsarxiv-cs-lg

// Survey on Multi-Agent Systems // The paper traces the landscape from classical paradigms (consensus, distributed control, swarm intellige…

// Survey on Multi-Agent Systems // The paper traces the landscape from classical paradigms (consensus, distributed control, swarm intelligence, cooperative learning) to foundation-model-enabled MAS (

safetydair-ai--x

The Role of Vocabularies in Learning Sparse Representations for Ranking

arXiv:2509.16621v2 Announce Type: replace-cross Abstract: Learned Sparse Retrieval (LSR) such as SPLADE has growing interest for effective semantic 1st stage matching while enjoying the efficiency of

WeatherArchive-Bench: Benchmarking Retrieval-Augmented Reasoning for Historical Weather Archives

arXiv:2510.05336v2 Announce Type: replace Abstract: Historical archives on weather events are collections of enduring primary source records that offer rich, untapped narratives of how societies have

We're open-sourcing FlashKDA — our high-performance CUTLASS-based implementation of Kimi Delta Attention kernels. Achieves 1.72×–2.22× prefi…

model-releaseskimi-moonshot--x

We're open-sourcing FlashKDA — our high-performance CUTLASS-based implementation of Kimi Delta Attention kernels. Achieves 1.72×–2.22× prefill speedup over the flash-linear-attention baseline on H20,

AscendKernelGen: A Systematic Study of LLM-Based Kernel Generation for Neural Processing Units

model-releasesarxiv-cs-ai

arXiv:2601.07160v2 Announce Type: replace Abstract: To meet the ever-increasing demand for computational efficiency, Neural Processing Units (NPUs) have become critical in modern AI infrastructure. Ho

Experience Compression Spectrum: Unifying Memory, Skills, and Rules in LLM Agents

arXiv:2604.15877v1 Announce Type: new Abstract: As LLM agents scale to long-horizon, multi-session deployments, efficiently managing accumulated experience becomes a critical bottleneck. Agent memory

InfoChess: A Game of Adversarial Inference and a Laboratory for Quantifiable Information Control

arXiv:2604.15373v1 Announce Type: cross Abstract: We propose InfoChess, a symmetric adversarial game that elevates competitive information acquisition to the primary objective. There is no piece captu

KRONE: Scalable LLM-Augmented Log Anomaly Detection via Hierarchical Abstraction

arXiv:2602.07303v3 Announce Type: replace-cross Abstract: Log anomaly detection is crucial for uncovering system failures and security risks. Although logs originate from nested component executions w

Spectral Tempering for Embedding Compression in Dense Passage Retrieval

arXiv:2603.19339v2 Announce Type: replace-cross Abstract: Dimensionality reduction is critical for deploying dense retrieval systems at scale, yet mainstream post-hoc methods face a fundamental trade-

AMA: Adaptive Memory via Multi-Agent Collaboration

arXiv:2601.20352v3 Announce Type: replace Abstract: The rapid evolution of Large Language Model (LLM) agents has necessitated robust memory systems to support cohesive long-term interaction and comple

Research

CURaTE: Continual Unlearning in Real Time with Ensured Preservation of LLM Knowledge

arXiv:2604.14644v1 Announce Type: new Abstract: The inability to filter out in advance all potentially problematic data from the pre-training of large language models has given rise to the need for me

researcharxiv-cs-cl

DeepPresenter: Environment-Grounded Reflection for Agentic Presentation Generation

arXiv:2602.22839v2 Announce Type: replace Abstract: Presentation generation requires deep content research, coherent visual design, and iterative refinement based on observation. However, existing pre

IROSA: Interactive Robot Skill Adaptation using Natural Language

arXiv:2603.03897v3 Announce Type: replace-cross Abstract: Foundation models have demonstrated impressive capabilities across diverse domains, while imitation learning provides principled methods for r

safetyarxiv-cs-cl

Tutorials

KnowRL: Exploring Knowledgeable Reinforcement Learning for Factuality

arXiv:2506.19807v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs), particularly slow-thinking models, often exhibit severe hallucination, outputting incorrect content due to an in

tutorialsarxiv-cs-cl

Million of recipes. Fuzzy ingredient data. One afternoon to solve it. 🍳⚡ Will Templeton, CTO and co-founder at Allspice, explains why Pinec…

Million of recipes. Fuzzy ingredient data. One afternoon to solve it. 🍳⚡ Will Templeton, CTO and co-founder at Allspice, explains why Pinecone is their fundamental building block: ❌ No weeks of cluste

applicationspinecone--x

On the Use of Evolutionary Optimization for the Dynamic Chance Constrained Open-Pit Mine Scheduling Problem

arXiv:2604.13385v1 Announce Type: cross Abstract: Open-pit mine scheduling is a complex real world optimization problem that involves uncertain economic values and dynamically changing resource capaci

RaTA-Tool: Retrieval-based Tool Selection with Multimodal Large Language Models

arXiv:2604.14951v1 Announce Type: cross Abstract: Tool learning with foundation models aims to endow AI systems with the ability to invoke external resources -- such as APIs, computational utilities,

safetyarxiv-cs-cl

Shuffle the Context: RoPE-Perturbed Self-Distillation for Long-Context Adaptation

arXiv:2604.14339v1 Announce Type: new Abstract: Large language models (LLMs) increasingly operate in settings that require reliable long-context understanding, such as retrieval-augmented generation a

TableNet A Large-Scale Table Dataset with LLM-Powered Autonomous

arXiv:2604.13041v1 Announce Type: cross Abstract: Table Structure Recognition (TSR) requires the logical reasoning ability of large language models (LLMs) to handle complex table layouts, but current

Text2Arch: A Dataset for Generating Scientific Architecture Diagrams from Natural Language Descriptions

arXiv:2604.14941v1 Announce Type: new Abstract: Communicating complex system designs or scientific processes through text alone is inefficient and prone to ambiguity. A system that automatically gener

A Comprehensive Survey on Network Traffic Synthesis: From Statistical Models to Deep Learning

arXiv:2507.01976v2 Announce Type: replace-cross Abstract: Synthetic network traffic generation has emerged as a promising alternative for various data-driven applications in the networking domain. It

applicationsarxiv-cs-lg

From Relevance to Authority: Authority-aware Generative Retrieval in Web Search Engines

arXiv:2604.13468v1 Announce Type: cross Abstract: Generative information retrieval (GenIR) formulates the retrieval process as a text-to-text generation task, leveraging the vast knowledge of large la

Lossless Prompt Compression via Dictionary-Encoding and In-Context Learning: Enabling Cost-Effective LLM Analysis of Repetitive Data

arXiv:2604.13066v1 Announce Type: new Abstract: In-context learning has established itself as an important learning paradigm for Large Language Models (LLMs). In this paper, we demonstrate that LLMs c

Memory Transfer Learning: How Memories are Transferred Across Domains in Coding Agents

arXiv:2604.14004v1 Announce Type: cross Abstract: Memory-based self-evolution has emerged as a promising paradigm for coding agents. However, existing approaches typically restrict memory utilization

Aethon: A Reference-Based Replication Primitive for Constant-Time Instantiation of Stateful AI Agents

arXiv:2604.12129v1 Announce Type: new Abstract: The transition from stateless model inference to stateful agentic execution is reshaping the systems assumptions underlying modern AI infrastructure. Wh

Characterizing Human Semantic Navigation in Concept Production as Trajectories in Embedding Space

arXiv:2602.05971v2 Announce Type: replace Abstract: Semantic representations can be framed as a structured, dynamic knowledge space through which humans navigate to retrieve and manipulate meaning. To

ChemDFM-R: A Chemical Reasoning LLM Enhanced with Atomized Chemical Knowledge

arXiv:2507.21990v4 Announce Type: replace-cross Abstract: Atomized chemical knowledge, such as functional group information of molecules and reactions, plays a pivotal intermediate role in the reasoni

Research

CoG: Controllable Graph Reasoning via Relational Blueprints and Failure-Aware Refinement over Knowledge Graphs

arXiv:2601.11047v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated remarkable reasoning capabilities but often grapple with reliability challenges like hallucinations.

researcharxiv-cs-cl

Continuous Knowledge Metabolism: Generating Scientific Hypotheses from Evolving Literature

arXiv:2604.12243v1 Announce Type: cross Abstract: Scientific hypothesis generation requires tracking how knowledge evolves, not just what is currently known. We introduce Continuous Knowledge Metaboli

safetyarxiv-cs-ai

Hardware

Fine-Tuning LLMs for Report Summarization: Analysis on Supervised and Unsupervised Data

arXiv:2503.10676v2 Announce Type: replace-cross Abstract: We study the efficacy of fine-tuning Large Language Models (LLMs) for the specific task of report (government archives, news, intelligence rep

hardwarearxiv-cs-ai

FlowPlan-G2P: A Structured Generation Framework for Transforming Scientific Papers into Patent Descriptions

arXiv:2601.02589v2 Announce Type: replace-cross Abstract: Over 3.5 million patents are filed annually, with drafting patent descriptions requiring deep technical and legal expertise. Transforming scie

From Myopic Selection to Long-Horizon Awareness: Sequential LLM Routing for Multi-Turn Dialogue

arXiv:2604.12385v1 Announce Type: new Abstract: Multi-turn dialogue is the predominant form of interaction with large language models (LLMs). While LLM routing is effective in single-turn settings, ex

safetyarxiv-cs-cl

GAM: Hierarchical Graph-based Agentic Memory for LLM Agents

arXiv:2604.12285v1 Announce Type: new Abstract: To sustain coherent long-term interactions, Large Language Model (LLM) agents must navigate the tension between acquiring new information and retaining

KG-Hopper: Empowering Compact Open LLMs with Knowledge Graph Reasoning via Reinforcement Learning

model-releasesarxiv-cs-ai

arXiv:2603.21440v4 Announce Type: replace-cross Abstract: Large Language Models (LLMs) demonstrate impressive natural language capabilities but often struggle with knowledge-intensive reasoning tasks.

Local-Splitter: A Measurement Study of Seven Tactics for Reducing Cloud LLM Token Usage on Coding-Agent Workloads

arXiv:2604.12301v1 Announce Type: cross Abstract: We present a systematic measurement study of seven tactics for reducing cloud LLM token usage when a small local model can act as a triage layer in fr

M^star: Every Task Deserves Its Own Memory Harness

arXiv:2604.11811v1 Announce Type: cross Abstract: Large language model agents rely on specialized memory systems to accumulate and reuse knowledge during extended interactions. Recent architectures ty

OVAL: Open-Vocabulary Augmented Memory Model for Lifelong Object Goal Navigation

arXiv:2604.12872v1 Announce Type: new Abstract: Object Goal Navigation (ObjectNav) refers to an agent navigating to an object in an unseen environment, which is an ability often required in the accomp

agentsarxiv-cs-ro

When to Forget: A Memory Governance Primitive

arXiv:2604.12007v1 Announce Type: new Abstract: Agent memory systems accumulate experience but currently lack a principled operational metric for memory quality governance -- deciding which memories t

Research

Attention Sinks as Internal Signals for Hallucination Detection in Large Language Models

arXiv:2604.10697v1 Announce Type: new Abstract: Large language models frequently exhibit hallucinations: fluent and confident outputs that are factually incorrect or unsupported by the input context.

researcharxiv-cs-cl

Beyond Fluency: Toward Reliable Trajectories in Agentic IR

arXiv:2604.04269v2 Announce Type: replace Abstract: Information Retrieval is shifting from passive document ranking toward autonomous agentic workflows that operate in multi-step Reason-Act-Observe lo

BLUEmed: Retrieval-Augmented Multi-Agent Debate for Clinical Error Detection

arXiv:2604.10389v1 Announce Type: new Abstract: Terminology substitution errors in clinical notes, where one medical term is replaced by a linguistically valid but clinically different term, pose a pe

CodeComp: Structural KV Cache Compression for Agentic Coding

arXiv:2604.10235v1 Announce Type: new Abstract: Agentic code tasks such as fault localization and patch generation require processing long codebases under tight memory constraints, where the Key-Value

local-aiarxiv-cs-cl

Compliant But Unsatisfactory: The Gap Between Auditing Standards and Practices for Probabilistic Genotyping Software

arXiv:2604.10875v1 Announce Type: cross Abstract: AI governance efforts increasingly rely on audit standards: agreed-upon practices for conducting audits. However, poorly designed standards can hide a

Deep-Reporter: Deep Research for Grounded Multimodal Long-Form Generation

arXiv:2604.10741v1 Announce Type: cross Abstract: Recent agentic search frameworks enable deep research via iterative planning and retrieval, reducing hallucinations and enhancing factual grounding. H

Diagnosing Retrieval vs. Utilization Bottlenecks in LLM Agent Memory

arXiv:2603.02473v2 Announce Type: replace Abstract: Memory-augmented LLM agents store and retrieve information from prior interactions, yet the relative importance of how memories are written versus h