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Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RL

arXiv:2607. 16204v1 Announce Type: new Abstract: Recent growth in reinforcement learning (RL) has surfaced a need for diverse, specialized training environments. Hand-curated environments with fixed task and reward difficulties become ineffective signals as model performance improves, and sparse rew

#확산언어모델#월드모델#에이전트RL

📰미디어arXiv cs.AI

원문

AI

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RAIL Guard: Closing the Evaluation-to-Remediation Gap in Responsible AI for LLM Agents

arXiv:2607. 16215v1 Announce Type: new Abstract: Existing guardrail systems for large language model agents operate as binary classifiers that block unsafe content, leaving organizations to discard failing outputs and retry from scratch. We introduce RAIL Guard, a closed-loop responsible AI pipeline

SelKV: Selective KV Cache Merging with Per-Token Merge-or-Drop and Attention Compensation

arXiv:2607. 16213v1 Announce Type: new Abstract: Large Language Models (LLMs) generate text autoregressively, relying on a key-value (KV) cache whose memory footprint grows linearly with context length, creating a major bottleneck. Recent compression methods mitigate this cost via token merging; how

Some Large Language Models Exhibit Consistent Risk Attitudes

arXiv:2607. 16197v1 Announce Type: new Abstract: As artificial intelligence systems are deployed in open-ended, high-stakes settings, a critical dimension remains unmeasured: how perceived risk is translated into action. We test whether large language models (LLMs) exhibit systematic and consistent

PlanFlip: Attacking Multi-Agent LLM Systems via Planning-Phase Prompt Injection

arXiv:2607. 16199v1 Announce Type: new Abstract: Multi-agent LLM systems increasingly rely on a Planner to decompose goals into sub-task sequences that downstream Executor and Critic agents execute and audit. We identify the planning phase as a critical attack surface: a single injection into the Pl

Rater State Bias in RLHF Preference Data: An Audit Framework

arXiv:2607. 16195v1 Announce Type: new Abstract: We identify a structured confound in Reinforcement Learning from Human Feedback (RLHF). Pairwise preference labels are intended to reflect the compared outputs, but they may also reflect the rater's state during annotation. Under sustained stressful o

Democratizing AI with Small Language Models: Structured Benchmarking and Parameter-Efficient Fine-Tuning for Local Deployment

arXiv:2607. 16202v1 Announce Type: new Abstract: AI democratization is not primarily a question of matching frontier-scale generality; it is a question of whether capable models can be selected, audited, and specialized under hardware and governance constraints that ordinary institutions can actuall

#소형언어모델#파라미터효율파인튜닝#로컬배포

Design and Validation of a Lightweight 1D CNN for Affective Touch Classification in Soft Plush Companions

arXiv:2607. 16196v1 Announce Type: new Abstract: Soft, sensorized companions offer a physically safe and emotionally intuitive interface for socially assistive technologies, yet their deformability and multichannel tactile sensing complicate the robust interpretation of human affect. This study pres

Deterministic Replay for AI Agent Systems

arXiv:2607. 16200v1 Announce Type: new Abstract: AI agent systems that couple large language models (LLMs) with external tools and APIs are inherently non-deterministic: LLM sampling variance, external API state, CDN infrastructure headers, and execution-environment noise collectively prevent any pr

A Survey on GNN-based Link Prediction: Techniques, Applications, and Challenges

arXiv:2607. 16198v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) have emerged as the leading paradigm for link prediction, enabling the inference of missing connections and the anticipation of potential future links. However, existing reviews lack systematic exploration specifically tar

Accurate and Efficient Long-Term Memory for LLM Agents

arXiv:2607. 16211v1 Announce Type: new Abstract: LLM agents augmented with persistent memory can recall past interactions, but existing systems suffer from two limitations: flat, unstructured storage loses relational context needed for multi-hop and temporal reasoning, and reliance on expensive LLM-

Generative Ontology Induction: Domain-Agnostic Schema Discovery from Document Corpora Using Large Language Models

arXiv:2607. 16201v1 Announce Type: new Abstract: Ontology engineering remains a critical bottleneck in knowledge-intensive AI systems. Existing automated approaches either depend on predefined schemas, operate within narrow domains, or produce unstructured outputs unsuitable for downstream pipelines

#온톨로지#지식그래프#LLM

📰미디어arXiv cs.AI

원문

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2026년 7월 21일 AI×블록체인 데일리 브리핑

2026년 6월 29일(월) ~ 7월 5일(일) AI×블록체인 주간 리포트

🆕 최신 글

Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RL

RAIL Guard: Closing the Evaluation-to-Remediation Gap in Responsible AI for LLM Agents

SelKV: Selective KV Cache Merging with Per-Token Merge-or-Drop and Attention Compensation

Some Large Language Models Exhibit Consistent Risk Attitudes

PlanFlip: Attacking Multi-Agent LLM Systems via Planning-Phase Prompt Injection

Rater State Bias in RLHF Preference Data: An Audit Framework

Democratizing AI with Small Language Models: Structured Benchmarking and Parameter-Efficient Fine-Tuning for Local Deployment

Design and Validation of a Lightweight 1D CNN for Affective Touch Classification in Soft Plush Companions

Deterministic Replay for AI Agent Systems

A Survey on GNN-based Link Prediction: Techniques, Applications, and Challenges

Accurate and Efficient Long-Term Memory for LLM Agents

Generative Ontology Induction: Domain-Agnostic Schema Discovery from Document Corpora Using Large Language Models

AI × BlockchainDaily Curation

2026년 7월 21일 AI×블록체인 데일리 브리핑

2026년 6월 29일(월) ~ 7월 5일(일) AI×블록체인 주간 리포트

🆕 최신 글

Masked Diffusion Language Models are Strong and Steerable Text-Based World Models for Agentic RL

RAIL Guard: Closing the Evaluation-to-Remediation Gap in Responsible AI for LLM Agents

SelKV: Selective KV Cache Merging with Per-Token Merge-or-Drop and Attention Compensation

Some Large Language Models Exhibit Consistent Risk Attitudes

PlanFlip: Attacking Multi-Agent LLM Systems via Planning-Phase Prompt Injection

Rater State Bias in RLHF Preference Data: An Audit Framework

Democratizing AI with Small Language Models: Structured Benchmarking and Parameter-Efficient Fine-Tuning for Local Deployment

Design and Validation of a Lightweight 1D CNN for Affective Touch Classification in Soft Plush Companions

Deterministic Replay for AI Agent Systems

A Survey on GNN-based Link Prediction: Techniques, Applications, and Challenges

Accurate and Efficient Long-Term Memory for LLM Agents

Generative Ontology Induction: Domain-Agnostic Schema Discovery from Document Corpora Using Large Language Models

AI × Blockchain
Daily Curation