Search: “retrieval”

arXiv:2607.22598v1 Announce Type: cross Abstract: Educational chatbots powered by large language models (LLMs) show promising effects on learning outcomes, yet most systems delegate pedagogical decisi

hardwarearxiv-cs-ai

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Model Releases

A Frozen 12B Beats Frontier Models on Verified Work: 100% Accuracy, 0 Tokens, Bit-Exact, Forever

DGX agent

arXiv:2607.23806v1 Announce Type: cross Abstract: Improving a language model today means retraining it: enormous compute, a new opaque model each cycle, non-deterministic output. We take the opposite

model-releasesarxiv-cs-ai

28 Jul 2026

ACM: Agentic Context Management for Long Horizon Tasks

arXiv:2607.23809v1 Announce Type: new Abstract: Agentic tasks are inherently long-horizon and multi-turn, constantly accumulating context through interactions with the environment. Existing context co

AutoMat: Enabling Automated Crystal Structure Reconstruction from Microscopy via Agentic Tool Use

arXiv:2505.12650v2 Announce Type: replace-cross Abstract: Reconstructing atomistic crystal structures from a single noisy STEM projection is an ill-posed inverse problem: multiple lattices can explain

Bringing Conversational Analytics to your entire data ecosystem

model-releasesgoogle-cloud-ai

Increasing the adoption of generative AI across the enterprise requires you to do more than deploy a generic chatbot with a custom wrapper. Interacting with business-critical databases demands absolut

Building AI That Works: ESnet's Pragmatic Approach to AI-Driven Operational Excellence

arXiv:2607.22948v1 Announce Type: cross Abstract: The ORBIT (Operations Responses and Business Intelligence Toolkit) project was initiated to assess agentic AI for the upcoming ESnet 7 initiative and

ClinFusion: A Vision-Centric Multimodal LLM System for Holistic Medical Understanding

arXiv:2607.24743v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) hold immense potential to revolutionize clinical practice, yet deploying them in the medical domain is fundam

ConsistencyGate: Preventing Memory Contamination in LLM Agents via Self-Consistency Admission Control

arXiv:2607.22962v1 Announce Type: new Abstract: LLM agents that operate over many turns accumulate facts in an external memory store and reuse them as premises for downstream reasoning. A hallucinated

Coordinated Networking for On-Device Agent-Augmented Real-Time Communication

arXiv:2607.22854v1 Announce Type: new Abstract: AI agents are enabling a new paradigm of agent-augmented real-time communication (RTC), where humans focus on high-level collaboration, while agents aut

Delegation Intelligence in Deep Search: A Controllable Framework for Disentangled Capability Diagnosis

arXiv:2607.23524v1 Announce Type: new Abstract: Deep search is becoming a core capability of modern agent systems, yet it is typically evaluated solely based on end-to-end answer accuracy. This couple

DishSeg24k: A Large-Scale Benchmark for Food Segmentation with Stochastic Expert Decoding

model-releasesarxiv-cs-cv

arXiv:2607.23070v1 Announce Type: new Abstract: Food segmentation is essential for applications such as intelligent catering, dietary assessment, and recommendation. However, existing benchmarks fail

DOSA: A Tree-Guided, Self-Regressive Framework for Long Document Structure Analysis

arXiv:2607.22679v1 Announce Type: new Abstract: In visually-rich documents, information is encoded not only in individual page objects such as tables, headers, and text blocks, but also in the structu

Hardware

Energy Constrained Hierarchical Underwater Monitoring via Local Multi-Agent RAG

arXiv:2607.24313v1 Announce Type: cross Abstract: Marine life monitoring is limited by strict energy constraints, poor underwater connectivity, and the high cost of transmitting raw multimodal data fr

hardwarearxiv-cs-cv

EventOD: Event-Aware OD Flow Generation via LLM-Guided Semantic Modulation

arXiv:2607.22655v1 Announce Type: new Abstract: Estimating origin-destination (OD) flows under disruptive events is important for disaster response and urban resilience. Existing deep OD models traine

Eviction as Estimation: A Fixed-Lag Smoothing View of Test-Time Memory, and When Measuring Beats Accumulating

arXiv:2607.24667v1 Announce Type: new Abstract: A language model with a bounded working memory must repeatedly decide which stored items to keep. Every deployed method decides the moment an item arriv

GTIN: A Unified Framework for Joint Event and Time Prediction in Temporal Graphs

arXiv:2607.23556v1 Announce Type: cross Abstract: Temporal graphs are increasingly used to model dynamic systems in diverse domains such as social networks, financial networks, and traffic networks. P

Head Avatars with Dynamic Explicit Hair

arXiv:2607.23861v1 Announce Type: new Abstract: We present DynHair, a novel method for tracking and modeling dynamic hair for human head avatars. From video input, we reconstruct a dynamic head avatar

researcharxiv-cs-cv

Tutorials

Integrating Factual and Normative Industrial Knowledge via Constraint-Aware Graph Attention for Process Plan Recommendation

arXiv:2607.24213v1 Announce Type: new Abstract: Integrating heterogeneous industrial knowledge, including factual relations and decision constraints, remains a core challenge in industrial information

tutorialsarxiv-cs-ai

KG2Code: Bridging Knowledge Graphs and Large Language Models via Executable Code for Question Answering

arXiv:2607.22652v1 Announce Type: new Abstract: Recent research has explored the integration of knowledge graphs (KGs) with large language models (LLMs) to enhance their performance on downstream know

Local Ai

LOCKS: Page-Local Compact Key Summaries for Efficient Long-Context Decoding

arXiv:2607.24555v1 Announce Type: cross Abstract: Serving large language models at long context is bottlenecked by the key-value (KV) cache, which is read in full at every decode step. Attention keys

local-aiarxiv-cs-ai

Making Mathematical Knowledge Explainable, Accessible and Interoperable Through Large Language Model Integration

arXiv:2607.24512v1 Announce Type: new Abstract: Mathematical models are central to formalizing research problems, yet their documentation often falls short of FAIR principles. Knowledge bases such as

MANGO: A Global Single-Date Paired Dataset for Mangrove Segmentation

arXiv:2601.17039v2 Announce Type: replace-cross Abstract: Mangroves are critical for climate-change mitigation, requiring reliable monitoring for effective conservation. While deep learning has emerge

MedLoCoMo: A Long-Context Multi-Session Medical Dialogue Benchmark for Large Language Models

arXiv:2607.22566v1 Announce Type: new Abstract: MedLoCoMo is a Medical Long-Context Memory benchmark for patient-specific clinical reasoning over multi-admission medical dialogue. Existing medical QA

PD^3: A Project Duplication Detection Framework via Adapted Multi-Agent Debate

arXiv:2505.17492v2 Announce Type: replace Abstract: Project duplication detection is critical for project quality assessment because it helps avoid investment in repeated proposals. Existing methods u

ProvenanceGuard: Source-Aware Factuality Verification for MCP-Based LLM Agents

arXiv:2606.18037v2 Announce Type: replace Abstract: Tool-using LLM agents increasingly use the Model Context Protocol (MCP) to answer from heterogeneous evidence sources, including search, APIs, datab

ReasFlow: Assisting Reasoning-Centric Scientific Discovery in Applied Mathematics via a Knowledge-Based Multi-Agent System

arXiv:2607.14178v2 Announce Type: replace Abstract: Recent advances in Large Language Models have fueled autonomous AI agents capable of tackling complex scientific tasks, yet existing automated resea

SAGE: Safety-First Defense-in-Depth Guardrails for Verified Lifecycle Control of High-Impact Generative AI

arXiv:2607.22926v1 Announce Type: new Abstract: High-impact generative AI makes catastrophic misuse a lifecycle-control problem, not merely a prompt-filtering problem. SAGE is a safety-first, authoriz

Same Question, Different Answers: Evaluating LLM Reliability Beyond Accuracy

arXiv:2607.22554v1 Announce Type: new Abstract: Large language models (LLMs) often achieve strong accuracy on benchmarks, yet it remains unclear how reliably they apply this knowledge when the same qu

SIREN: Towards End-to-End Extreme-Weather Early Warning with Experience-Grounded LLM Agents

arXiv:2607.24588v1 Announce Type: new Abstract: Early warning of extreme weather is essential for mitigating the societal, economic, and environmental risks posed by hazardous weather events. However,

Local Ai

TaoMate: Anchor-Guided Memory Bridging Evolving and Reference States for Real-Time Audio-Video Digital Human Generation

arXiv:2607.24359v1 Announce Type: new Abstract: Real-time long-form digital-human generation relies on causal models to extend audio-visual content while preserving subject appearance and audio-video

local-aiarxiv-cs-cv

Too much evidence, too little time: From text to actionable recommendations through multi-objective evidence reasoning

arXiv:2607.22574v1 Announce Type: new Abstract: Evidence-based clinical decision making requires specialists to identify, evaluate and synthesize relevant scientific literature. However, PubMed search

Torq unveils SOC Brain, a self-learning layer for its AI SOC platform

Security hyperautomation platform company Torq Ltd. today introduced Torq SOC Brain, a new layer of its artificial intelligence security operations center platform that trains on a customer’s own inve

agentssiliconangle

TRACE-CTI: Auditable Post-Extraction Governance of TTP Claims with Knowledge Graphs

arXiv:2607.24563v1 Announce Type: new Abstract: Security Operations Centers increasingly rely on automated mapping of Cyber Threat Intelligence reports to MITRE ATT&CK, yet extractor outputs remain fa

Try Once, Then Optimal: De-Redundified Procedure Memory for Cross-Episode Exploration Amortization

model-releasesarxiv-cs-ro

arXiv:2607.23702v1 Announce Type: new Abstract: Manipulating objects with hidden internal state, such as a latched microwave, forces a robot to probe before it can act. Yet a robot that has solved an

Verification-Notebook Learning for Source-Aware Multimodal Misinformation Detection

arXiv:2607.23581v1 Announce Type: new Abstract: Multimodal misinformation verification is challenging because misleading signals may come from different parts of a post and require different forms of

What Can I Edit? Open-Ended Strategy Discovery and the Emotion Editability Landscape

arXiv:2607.23920v1 Announce Type: new Abstract: Emotional image editing requires more than applying affective filters or modifying predefined visual factors: an effective edit must identify what a par

agentsarxiv-cs-cv

What CLIP Knows but Cannot Say: Recovering Negation from Frozen Intermediate Features

arXiv:2607.23271v1 Announce Type: cross Abstract: Contrastive vision-language models such as CLIP map semantically opposite phrases (e.g., 'a dog' vs. 'not a dog') to nearly identical embeddings, rend

What Softmax Throws Away: Mass-Aware Attention for Evidence Accumulation

arXiv:2607.22781v1 Announce Type: cross Abstract: High task performance does not show whether a model retains prediction-relevant structural information in its internal representation. Temporal graph

When Low CER is Not Enough: An Analysis of Hallucinations in Vision-Language OCR Systems on Historical Uruguayan Documents

model-releasesarxiv-cs-cv

arXiv:2607.24077v1 Announce Type: new Abstract: Optical Character Recognition (OCR) is a key component in the digitization of historical archives. Recently, Vision-Language Models (VLMs) have emerged

A Factorial Study of Synthetic Data Generation for Low-Resource Machine Translation using Grammar Books

arXiv:2607.22376v1 Announce Type: new Abstract: Most endangered languages lack the parallel data required for machine translation, despite the existence of descriptive grammar books. We introduce a pi

researcharxiv-cs-cl

Local Ai

Built a local-first workflow automation platform around Ollama - now at v0.11.0

I've been working on an open-source workflow automation platform over the past few months, with Ollama as one of the first-class providers rather than treating it as an afterthought. The goal wasn't t

local-air-ollama

Do Modules Stay in Their Lane? Role Drift in Compound LLM Systems

arXiv:2607.21627v1 Announce Type: cross Abstract: End-to-end reinforcement learning can improve the accuracy of compound LLM systems, but it does not constrain how modules divide labor internally. We

safetyarxiv-cs-lg

Great technical paper from Harvard and MIT. It's on role drift in compound LLM systems. (bookmark it) End-to-end RL improves the accuracy of…

Great technical paper from Harvard and MIT. It's on role drift in compound LLM systems. (bookmark it) End-to-end RL improves the accuracy of a multi-module LLM pipeline without constraining how the mo

safetydair-ai--x

Learning What Matters: Supervising Sparse Attention Routing with Causal Evidence Sets

model-releasesarxiv-cs-cl

arXiv:2607.21692v1 Announce Type: cross Abstract: Sparse attention reduces the cost of long contexts by allowing each query to read only selected parts of the input. These selectors are often trained

MedKGent: A Large Language Model Agent Framework for Constructing Temporally Evolving Medical Knowledge Graph

arXiv:2508.12393v3 Announce Type: replace Abstract: The rapid expansion of medical literature challenges the scalable structuring of domain knowledge. Knowledge Graphs (KGs) offer a solution, yet curr

agentsarxiv-cs-cl

Reliability Scales Inversely: Bigger Language Models Compound Mistakes Faster

arXiv:2607.18292v2 Announce Type: replace-cross Abstract: As language models scale, answers start truer but degrade faster: scaling buys capability but erodes reliability. The knowledge-gap account --

safetyarxiv-cs-cl

Hardware

RIS-Kernel: A Model-Agnostic Architecture for Long-Context LLM Inference via Sparse Attention

arXiv:2607.21927v1 Announce Type: new Abstract: Full self-attention in large language models scales as O(N^2), which limits long-context document analysis to 65,536 tokens and requires costly GPU clus

hardwarearxiv-cs-lg

Applications

Teachy Mini: Development and Preliminary Evaluation of a Knowledge-Based Generative Social Robot for Higher Education

arXiv:2607.22345v1 Announce Type: new Abstract: Generative social robots (GSRs) powered by large language models offer new possibilities for personalized tutoring in higher education, but also introdu

applicationsarxiv-cs-ro