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🔬 RESEARCH

Actionable Activation Directions for Detecting and Mitigating Emergent Misalignment Across Language Model Families

via Arxiv 👤 Abdul Rafay Syed 📅 2026-06-18

⚡ Score: 8.1

"Fine-tuning language models on insecure code induces emergent misalignment with poorly understood internal structure. We investigate whether this misalignment corresponds to a causally actionable activation-space direction shared across architectures. Across four instruction-tuned model families (Qw..."

🔬 RESEARCH

Calibration Without Comprehension: Diagnosing the Limits of Fine-Tuning LLMs for Vulnerability Detection in Systems Software

via Arxiv 👤 Arastoo Zibaeirad, Marco Vieira 📅 2026-06-18

⚡ Score: 7.4

"Whether LLMs scoring well on vulnerability benchmarks genuinely reason about security or merely pattern-match on contaminated data remains unresolved. We present CWE-Trace, a framework for LLM vulnerability detection built from 834 manually curated Linux kernel samples spanning 74 CWEs. The framewor..."

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Form Before Data: The Real Bottleneck for Physical AI

via HackerNews 👤 adlrocha 📅 2026-06-21

🔺 1 pts ⚡ Score: 7.3

🔬 RESEARCH

Execution-State Capsules: Graph-Bound Execution-State Checkpoint and Restore for Low-Latency, Small-Batch, On-Device Physical-AI Serving

via Arxiv 👤 Liang Su 📅 2026-06-18

⚡ Score: 7.2

"Mainstream LLM serving systems reuse prefix work mainly through paged or radix key-value (KV) caches. This is highly effective for high-throughput, high-concurrency serving, but it manages only one positional fragment of execution state: the KV cache. We study the opposite regime: low-latency, small..."

🔬 RESEARCH

How Transparent is DiffusionGemma?

via Arxiv 👤 Joshua Engels, Callum McDougall, Bilal Chughtai et al. 📅 2026-06-18

⚡ Score: 7.0

"LLM reasoning transparency is a critical affordance for understanding model decisions, mitigating misuse and misalignment, and debugging surprising model behaviors. However, DiffusionGemma performs a larger fraction of its computation in a continuous latent space; does this make its reasoning less t..."

📰 NEWS

Moving Machine Learning into the Analog Domain

via HackerNews 👤 random__duck 📅 2026-06-21

🔺 4 pts ⚡ Score: 7.0

🔬 RESEARCH

Beyond Global Replanning: Hierarchical Recovery for Cross-Device Agent Systems

via Arxiv 👤 Shu Yao, Yuhua Luo, Qian Long et al. 📅 2026-06-18

⚡ Score: 6.9

"Real-world computer-use tasks often span multiple applications and devices, requiring agents to coordinate heterogeneous environments under dynamic runtime failures. Existing multi-device agent systems support task decomposition and cross-device assignment, but recovery remains largely coarse-graine..."

🔬 RESEARCH

What Do Safety-Aligned LLMs Learn From Mixed Compliance Demonstrations?

via Arxiv 👤 Sihui Dai, Mann Patel 📅 2026-06-18

⚡ Score: 6.9

"Prior work has shown that in-context demonstrations can jailbreak language models, but it remains unclear how models interpret different types of compliance demonstrations. We study this by mixing benign compliance demonstrations (non-harmful request, helpful response) with harmful compliance demons..."

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Show HN: Lelu – catch AI agents when they're manipulated at runtime

via HackerNews 👤 Abenezer0923 📅 2026-06-21

🔺 2 pts ⚡ Score: 6.8

🔬 RESEARCH

Sovereign Execution Brokers: Enforcing Certificate-Bound Authority in Agentic Control Planes

via Arxiv 👤 Jun He, Deying Yu 📅 2026-06-18

⚡ Score: 6.8

"Autonomous agents are increasingly connected to cloud, deployment, and data-control workflows, but production mutation authority should not reside inside non-deterministic reasoning processes. Existing access-control mechanisms authorize identities, while assurance layers certify proposed actions; n..."

📰 NEWS

Governing AI-agent actions via a network intent layer (NILScript)

via HackerNews 👤 bashierkh 📅 2026-06-21

🔺 1 pts ⚡ Score: 6.8

🔬 RESEARCH

Contagion Networks: Evaluator Bias Propagation in Multi-Agent LLM Systems

via Arxiv 👤 Zewen Liu 📅 2026-06-18

⚡ Score: 6.7

"When large language models serve as evaluators in multi-agent systems, their systematic evaluation biases propagate through the agent network. We introduce Contagion Networks, a formal framework for measuring how evaluator biases spread across interacting LLM agents. In a controlled 3-agent experime..."

🔬 RESEARCH

Efficient and Sound Probabilistic Verification for AI Agents

via Arxiv 👤 Alaia Solko-Breslin, Pramod Kaushik Mudrakarta, Mihai Christodorescu et al. 📅 2026-06-18

⚡ Score: 6.7

"Securing AI agents that operate in complex digital environments has become a critical need, and runtime monitoring approaches that formulate and enforce policies expressed in a formal language like Datalog offer a promising solution. However, existing approaches are restricted to deterministic polic..."

🔬 RESEARCH

LedgerAgent: Structured State for Policy-Adherent Tool-Calling Agents

via Arxiv 👤 Md Nayem Uddin, Amir Saeidi, Eduardo Blanco et al. 📅 2026-06-18

⚡ Score: 6.6

"Policy-adherent tool-calling agents in customer-service domains must maintain task states across turns while calling tools and obeying domain policies. Task states consist of relevant facts, identifiers, constraints, and conditions observed through user interaction and tool calls. In standard agents..."

🔬 RESEARCH

Token-Operations-Oriented Inference Optimization Techniques for Large Models

via Arxiv 👤 Shiguo Lian, Kai Wang, Zhaoxiang Liu et al. 📅 2026-06-18

⚡ Score: 6.5

"Large model inference optimization serves as a key foundation for supporting the scalable, low-cost, and highly stable operation of large model services. Centered on token-oriented inference optimization technology, this paper proposes for the first time a four-layer technical architecture consistin..."

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Show HN: shared verified memory for AI agents: one learns, all recall

via HackerNews 👤 kage18 📅 2026-06-21

🔺 1 pts ⚡ Score: 6.2

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Show HN: GreyFox – Free self-hosted AI proxy, token quotas, and local cache

via HackerNews 👤 SkilfulFox 📅 2026-06-21

🔺 2 pts ⚡ Score: 6.1

🔬 RESEARCH

FlowEdit: Associative Memory for Lifelong Pronunciation Adaptation in Flow-Matching TTS

via Arxiv 👤 Harshit Singh, Ayush Pratap Singh, Nityanand Mathur 📅 2026-06-18

⚡ Score: 6.1

"Flow-matching text-to-speech systems achieve remarkable zero-shot quality but remain static after deployment: pronunciation errors on out-of-vocabulary proper nouns persist unless the model is retrained. We introduce FlowEdit, a life-long adaptation framework for frozen flow-matching TTS that learns..."

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Show HN: Argybargy – A peer-to-peer bridge connecting any AI agents and sessions

via HackerNews 👤 titusblair 📅 2026-06-21

🔺 2 pts ⚡ Score: 6.1

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