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đŦ RESEARCH
via Arxiv
đ¤ Abdul Rafay Syed
đ
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..."
đŦ RESEARCH
via Arxiv
đ¤ Jun He, Deying Yu
đ
2026-06-18
⥠Score: 8.0
"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..."
đ° NEWS
đē 9 pts
⥠Score: 7.5
đŦ RESEARCH
via Arxiv
đ¤ Robi Rahman, Sabiha Tajdari
đ
2026-06-17
⥠Score: 7.3
"Hardware-enabled monitoring of GPU workloads underpins many proposals for AI compute governance, but if developers can defeat monitoring mechanisms, such schemes are unworkable. We evaluate the adversarial robustness of GPU workload classification using only zero-overhead, privacy-preserving NVML te..."
đ° NEWS
đē 1 pts
⥠Score: 7.1
đ° NEWS
đē 4 pts
⥠Score: 7.1
đŦ RESEARCH
via Arxiv
đ¤ Joshua Engels, Callum McDougall, Bilal Chughtai et al.
đ
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..."
đŦ RESEARCH
via Arxiv
đ¤ Sihui Dai, Mann Patel
đ
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..."
đ° NEWS
đē 3 pts
⥠Score: 6.9
đŦ RESEARCH
via Arxiv
đ¤ Shaghayegh Kolli, Timo Cavelius, Nafiseh Nikeghbal et al.
đ
2026-06-18
⥠Score: 6.8
"Multimodal large language models (MLLMs) are increasingly deployed in personally and societally consequential settings, yet the visual cues that shape how these models judge people remain poorly understood. Prior work often compares different (groups of) individuals, making it difficult to separate..."
đŦ RESEARCH
via Arxiv
đ¤ Arastoo Zibaeirad, Marco Vieira
đ
2026-06-18
⥠Score: 6.8
"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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đŦ RESEARCH
via Arxiv
đ¤ Siyi Gu, Jialin Chen, Sophia Zhou et al.
đ
2026-06-17
⥠Score: 6.8
"Post-training of reasoning language models is commonly driven by supervised distillation and reinforcement learning with verifiable rewards. Distillation often relies on chain-of-thought annotations that are expensive to obtain and may themselves be noisy, incomplete, or partially incorrect; even wh..."
đŦ RESEARCH
via Arxiv
đ¤ Ruida Wang, Rui Pan, Pengcheng Wang et al.
đ
2026-06-17
⥠Score: 6.8
"Enhancing the formal math reasoning capabilities of Large Language Models (LLMs) has become a key focus in both mathematical and computer science communities in recent years. While significant progress has been made in using state-of-the-art Auto-Regressive (AR) LLMs for formal theorem proving, thes..."
đŦ RESEARCH
via Arxiv
đ¤ Shu Yao, Yuhua Luo, Qian Long et al.
đ
2026-06-18
⥠Score: 6.7
"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..."
đŦ RESEARCH
"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..."
đŦ RESEARCH
via Arxiv
đ¤ Alaia Solko-Breslin, Pramod Kaushik Mudrakarta, Mihai Christodorescu et al.
đ
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..."
đŦ RESEARCH
via Arxiv
đ¤ Haipeng Luo, Qingfeng Sun, Songli Wu et al.
đ
2026-06-17
⥠Score: 6.7
"Reinforcement Learning with Verifiable Rewards algorithms like GRPO have emerged as the dominant post-training paradigm for complex reasoning in LLMs, yet commonly suffer from policy entropy collapse during training. We conduct a first-order gradient analysis of token-level entropy dynamics under GR..."
đŦ RESEARCH
via Arxiv
đ¤ Anoushka Vyas, Aarushi Dhanuka, Sina Khoshfetrat Pakazad et al.
đ
2026-06-17
⥠Score: 6.7
"Production data integration is bottlenecked by repeated, lossy handoffs between data owners, engineers, and analysts who must collaboratively discover, structure, and query enterprise data. We present Data Intelligence Agents (DIA), a system of three agents (Data Interpreter, Schema Creator, and Que..."
đŦ RESEARCH
via Arxiv
đ¤ Aueaphum Aueawatthanaphisut
đ
2026-06-18
⥠Score: 6.6
"Real-world clinical decision support requires reasoning over heterogeneous and longitudinal patient information rather than answering isolated medical questions. However, current medical large language models and retrieval-augmented generation systems often rely on single-step prompting or retrieval..."
đŦ RESEARCH
via Arxiv
đ¤ Md Nayem Uddin, Amir Saeidi, Eduardo Blanco et al.
đ
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..."
đŦ RESEARCH
via Arxiv
đ¤ Zirui Wu, Lin Zheng, Jiacheng Ye et al.
đ
2026-06-17
⥠Score: 6.6
"Block diffusion language models accelerate decoding through parallel block-wise denoising, yet whether they can be reliably scaled for long chain-of-thought (CoT) reasoning remains unresolved. To this end, we develop DreamReasoner-8B, an open-source block diffusion reasoning model, and conduct a sys..."
đŦ RESEARCH
via Arxiv
đ¤ Amiri Hayes, Belinda Li, Jacob Andreas
đ
2026-06-17
⥠Score: 6.6
"A longstanding goal of research on interpretable deep learning is to replace opaque neural computations with human-meaningful symbolic descriptions. In this paper, we propose an approach for approximating the behavior of components of deep networks with executable programs. We focus on attention hea..."
đŦ RESEARCH
via Arxiv
đ¤ Shiguo Lian, Kai Wang, Zhaoxiang Liu et al.
đ
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..."
đŦ RESEARCH
via Arxiv
đ¤ Yijin Wang, Shuyi Wang, Wenhan Zhang et al.
đ
2026-06-17
⥠Score: 6.5
"Text-rich images often contain privacy-sensitive, transactional, or decision-relevant information. As recent multimodal image generation models become increasingly capable of synthesizing realistic textual content and structured visual designs, detecting AI-generated text-rich images has become an i..."
đŦ RESEARCH
via Arxiv
đ¤ Yingshan Susan Wang, Cedegao E. Zhang, Linlu Qiu et al.
đ
2026-06-17
⥠Score: 6.4
"Learning to simulate human users in interactive settings could advance the training of agent assistants, evaluation of personalization systems, research in the social sciences, and more. Existing approaches generally do so by training a large language model (LLM) to match a single ground truth respo..."
đ ī¸ SHOW HN
đē 3 pts
⥠Score: 6.2
đ° NEWS
đē 2 pts
⥠Score: 6.2
đ° NEWS
đē 1 pts
⥠Score: 6.1
đ° NEWS
đē 2 pts
⥠Score: 6.1
đ ī¸ SHOW HN
đē 2 pts
⥠Score: 6.1
đ ī¸ SHOW HN
đē 2 pts
⥠Score: 6.1
đŦ RESEARCH
via Arxiv
đ¤ Zhenghao Xing, Ruiyang Xu, Yuxuan Wang et al.
đ
2026-06-17
⥠Score: 6.1
"Passive models for long video understanding typically rely on a "watch-it-all" paradigm, processing frames uniformly regardless of query difficulty, causing computational cost to grow with video duration. Although interactive frameworks have emerged, they often rely on global pre-scanning, and their..."