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🔬 RESEARCH
via Arxiv
👤 Mingqian Feng, Xiaodong Liu, Weiwei Yang et al.
📅 2026-02-06
⚡ Score: 7.8
"Multi-turn jailbreaks capture the real threat model for safety-aligned chatbots, where single-turn attacks are merely a special case. Yet existing approaches break under exploration complexity and intent drift. We propose SEMA, a simple yet effective framework that trains a multi-turn attacker witho..."
🏢 BUSINESS
🎯 Semiconductor manufacturing monopolies • Geopolitics of semiconductor production • Taiwan's semiconductor industry vulnerability
💬 "The days of cheap computing have been in decline and are now dead"
• "Taiwan will no longer have any value worth protecting"
🔬 RESEARCH
"We just released v1 of a domain-specific neuroscience/BCI multiple-choice eval (500 questions).
A few things surprised us enough to share:
* Eval generated in a single pass under strict constraints (no human review, no regeneration, no polishing).
* Despite that, frontier models cluster very..."
🔬 RESEARCH
via Arxiv
👤 Jian Chen, Yesheng Liang, Zhijian Liu
📅 2026-02-05
⚡ Score: 7.3
"Autoregressive large language models (LLMs) deliver strong performance but require inherently sequential decoding, leading to high inference latency and poor GPU utilization. Speculative decoding mitigates this bottleneck by using a fast draft model whose outputs are verified in parallel by the targ..."
🔬 RESEARCH
via Arxiv
👤 Tiansheng Hu, Yilun Zhao, Canyu Zhang et al.
📅 2026-02-05
⚡ Score: 7.0
"Deep research agents have emerged as powerful systems for addressing complex queries. Meanwhile, LLM-based retrievers have demonstrated strong capability in following instructions or reasoning. This raises a critical question: can LLM-based retrievers effectively contribute to deep research agent wo..."
🔬 RESEARCH
via Arxiv
👤 Grace Luo, Jiahai Feng, Trevor Darrell et al.
📅 2026-02-06
⚡ Score: 6.9
"Existing approaches for analyzing neural network activations, such as PCA and sparse autoencoders, rely on strong structural assumptions. Generative models offer an alternative: they can uncover structure without such assumptions and act as priors that improve intervention fidelity. We explore this..."
🔬 RESEARCH
via Arxiv
👤 Jian Chen, Zhuoran Wang, Jiayu Qin et al.
📅 2026-02-05
⚡ Score: 6.9
"Large language models rely on kv-caches to avoid redundant computation during autoregressive decoding, but as context length grows, reading and writing the cache can quickly saturate GPU memory bandwidth. Recent work has explored KV-cache compression, yet most approaches neglect the data-dependent n..."
🔬 RESEARCH
via Arxiv
👤 Wei Liu, Jiawei Xu, Yingru Li et al.
📅 2026-02-05
⚡ Score: 6.8
"High-quality kernel is critical for scalable AI systems, and enabling LLMs to generate such code would advance AI development. However, training LLMs for this task requires sufficient data, a robust environment, and the process is often vulnerable to reward hacking and lazy optimization. In these ca..."
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🔬 RESEARCH
via Arxiv
👤 Miranda Muqing Miao, Young-Min Cho, Lyle Ungar
📅 2026-02-05
⚡ Score: 6.8
"Large language models (LLMs) exhibit persistent miscalibration, especially after instruction tuning and preference alignment. Modified training objectives can improve calibration, but retraining is expensive. Inference-time steering offers a lightweight alternative, yet most existing methods optimiz..."
🔬 RESEARCH
via Arxiv
👤 Yuxing Lu, Yucheng Hu, Xukai Zhao et al.
📅 2026-02-05
⚡ Score: 6.8
"Multi-agent systems built from prompted large language models can improve multi-round reasoning, yet most existing pipelines rely on fixed, trajectory-wide communication patterns that are poorly matched to the stage-dependent needs of iterative problem solving. We introduce DyTopo, a manager-guided..."
🔬 RESEARCH
via Arxiv
👤 Alex McKenzie, Keenan Pepper, Stijn Servaes et al.
📅 2026-02-06
⚡ Score: 6.7
"Large language models can resist task-misaligned activation steering during inference, sometimes recovering mid-generation to produce improved responses even when steering remains active. We term this Endogenous Steering Resistance (ESR). Using sparse autoencoder (SAE) latents to steer model activat..."
🔬 RESEARCH
via Arxiv
👤 Saad Hossain, Tom Tseng, Punya Syon Pandey et al.
📅 2026-02-06
⚡ Score: 6.7
"As increasingly capable open-weight large language models (LLMs) are deployed, improving their tamper resistance against unsafe modifications, whether accidental or intentional, becomes critical to minimize risks. However, there is no standard approach to evaluate tamper resistance. Varied data sets..."
🔬 RESEARCH
via Arxiv
👤 Yuchen Yan, Liang Jiang, Jin Jiang et al.
📅 2026-02-06
⚡ Score: 6.6
"Large reasoning models achieve strong performance by scaling inference-time chain-of-thought, but this paradigm suffers from quadratic cost, context length limits, and degraded reasoning due to lost-in-the-middle effects. Iterative reasoning mitigates these issues by periodically summarizing interme..."
🔬 RESEARCH
via Arxiv
👤 Lizhuo Luo, Shenggui Li, Yonggang Wen et al.
📅 2026-02-05
⚡ Score: 6.6
"Diffusion large language models (dLLMs) have emerged as a promising alternative for text generation, distinguished by their native support for parallel decoding. In practice, block inference is crucial for avoiding order misalignment in global bidirectional decoding and improving output quality. How..."
🔬 RESEARCH
via Arxiv
👤 Xianyang Liu, Shangding Gu, Dawn Song
📅 2026-02-05
⚡ Score: 6.6
"Large language model (LLM)-based agents are increasingly expected to negotiate, coordinate, and transact autonomously, yet existing benchmarks lack principled settings for evaluating language-mediated economic interaction among multiple agents. We introduce AgenticPay, a benchmark and simulation fra..."
🛠️ TOOLS
🎯 Debate over LLM coding agents • Compiler complexity and limitations • Trajectory of LLM-generated compilers
💬 "The comparison was invited. It turned out (for whatever reason) that CCC failed to compile the Linux kernel when GCC could."
• "Rust is a bad language for the test, as a first target, if you want an LLM-coded Rust C compiler, and you have LLM experience, you would go - C compiler - Rust port."
🔬 RESEARCH
via Arxiv
👤 Yining Lu, Meng Jiang
📅 2026-02-06
⚡ Score: 6.5
"We study a persistent failure mode in multi-objective alignment for large language models (LLMs): training improves performance on only a subset of objectives while causing others to degrade. We formalize this phenomenon as cross-objective interference and conduct the first systematic study across c..."
🔬 RESEARCH
via Arxiv
👤 Junxiong Wang, Fengxiang Bie, Jisen Li et al.
📅 2026-02-06
⚡ Score: 6.5
"Speculative decoding can significantly accelerate LLM serving, yet most deployments today disentangle speculator training from serving, treating speculator training as a standalone offline modeling problem. We show that this decoupled formulation introduces substantial deployment and adaptation lag:..."
🌐 POLICY
"External link discussion - see full content at original source."
🎯 AI opacity • AI business models • AI transparency
💬 "AI companies keep their models opaque on purpose"
• "Transparency is the losing strategy under current US regulation"
🔬 RESEARCH
via Arxiv
👤 Haozhen Zhang, Haodong Yue, Tao Feng et al.
📅 2026-02-05
⚡ Score: 6.5
"Memory is increasingly central to Large Language Model (LLM) agents operating beyond a single context window, yet most existing systems rely on offline, query-agnostic memory construction that can be inefficient and may discard query-critical information. Although runtime memory utilization is a nat..."
🔬 RESEARCH
via Arxiv
👤 Ruchika Chavhan, Malcolm Chadwick, Alberto Gil Couto Pimentel Ramos et al.
📅 2026-02-06
⚡ Score: 6.4
"While large-scale text-to-image diffusion models continue to improve in visual quality, their increasing scale has widened the gap between state-of-the-art models and on-device solutions. To address this gap, we introduce NanoFLUX, a 2.4B text-to-image flow-matching model distilled from 17B FLUX.1-S..."
🔬 RESEARCH
via Arxiv
👤 John Kirchenbauer, Abhimanyu Hans, Brian Bartoldson et al.
📅 2026-02-05
⚡ Score: 6.4
"Existing techniques for accelerating language model inference, such as speculative decoding, require training auxiliary speculator models and building and deploying complex inference pipelines. We consider a new approach for converting a pretrained autoregressive language model from a slow single ne..."
🔬 RESEARCH
via Arxiv
👤 Shuo Nie, Hexuan Deng, Chao Wang et al.
📅 2026-02-05
⚡ Score: 6.2
"As large language models become smaller and more efficient, small reasoning models (SRMs) are crucial for enabling chain-of-thought (CoT) reasoning in resource-constrained settings. However, they are prone to faithfulness hallucinations, especially in intermediate reasoning steps. Existing mitigatio..."
🔬 RESEARCH
via Arxiv
👤 Tian Lan, Felix Henry, Bin Zhu et al.
📅 2026-02-06
⚡ Score: 6.1
"Current Information Seeking (InfoSeeking) agents struggle to maintain focus and coherence during long-horizon exploration, as tracking search states, including planning procedure and massive search results, within one plain-text context is inherently fragile. To address this, we introduce \textbf{Ta..."
🔬 RESEARCH
via Arxiv
👤 Jiangping Huang, Wenguang Ye, Weisong Sun et al.
📅 2026-02-06
⚡ Score: 6.1
"Large Language Models (LLMs) often generate code with subtle but critical bugs, especially for complex tasks. Existing automated repair methods typically rely on superficial pass/fail signals, offering limited visibility into program behavior and hindering precise error localization. In addition, wi..."
🔬 RESEARCH
via Arxiv
👤 Dingwei Zhu, Zhiheng Xi, Shihan Dou et al.
📅 2026-02-05
⚡ Score: 6.1
"Training reinforcement learning (RL) systems in real-world environments remains challenging due to noisy supervision and poor out-of-domain (OOD) generalization, especially in LLM post-training. Recent distributional RL methods improve robustness by modeling values with multiple quantile points, but..."
🔬 RESEARCH
via Arxiv
👤 Junxiao Liu, Zhijun Wang, Yixiao Li et al.
📅 2026-02-05
⚡ Score: 6.1
"Long reasoning models often struggle in multilingual settings: they tend to reason in English for non-English questions; when constrained to reasoning in the question language, accuracies drop substantially. The struggle is caused by the limited abilities for both multilingual question understanding..."
🤖 AI MODELS
🎯 Code quality foundations • AI-assisted development limitations • Responsible AI usage
💬 "The code foundation is everything."
• "Don't let AI write code for you unless it's something trivial."