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🔬 RESEARCH
"Transformer prefill reuses weights across tokens and is dominated by matrix multiplication and activation data movement; single-token decode has limited reuse and is dominated by weight and KV-cache reads. We present FUTRANSFORMER, a CUDA implementation of a Llama-style Transformer block for NVIDIA..."
🔬 RESEARCH
🎯 Model looping problems • Reasoning vs thinking debate • Latent space architecture
💬 "It got stuck in a thinking loop forever and simply could not finish the task"
• "There is no thinking. Its a function that takes ~500k words, and returns some words"
🔬 RESEARCH
via Arxiv
👤 Dongyoon Hahm, Woogyeol Jin, Dennis Wei et al.
📅 2026-10-16
⚡ Score: 7.3
"Fine-tuning large language models (LLMs) can induce behaviors beyond those explicitly targeted. For example, training a model to respond more warmly can make it more sycophantic, and training it to write insecure code can cause broad misalignment on prompts unrelated to coding. We refer to a relatio..."
🔬 RESEARCH
via Arxiv
👤 Jiaming Xu, Hanzhen Wang, Tianlang Zhao et al.
📅 2026-10-16
⚡ Score: 7.0
"Speculative decoding has become a mainstream technique for accelerating large language model (LLM) inference by using a lightweight draft model to generate candidate tokens that are subsequently verified by the target model. However, agentic workloads introduce long and continuously evolving context..."
🔬 RESEARCH
via Arxiv
👤 Jinho Choi, Hyesu Lim, Jaegul Choo et al.
📅 2026-10-16
⚡ Score: 7.0
"Sparse autoencoders (SAEs) explain foundation model representations by decomposing activations into sparse combinations of learned dictionary atoms. However, the learned dictionaries can vary across training runs, limiting the reliability and reproducibility of SAE-based analyses. We propose Consist..."
🔬 RESEARCH
via Arxiv
👤 Chiatzen Wang, Bill Xu, Haochen Gu et al.
📅 2026-10-16
⚡ Score: 6.9
"Speculative decoding typically characterizes speedup by draft tokens accepted per verification round. Lossless verification preserves the target model's output distribution and thus expected completion length, making this metric a meaningful efficiency proxy. Relaxed (lossy) verification accepts tok..."
🔬 RESEARCH
via Arxiv
👤 Shangheng Du, Jinxin Shi, Shuaiyu Zhang et al.
📅 2026-10-15
⚡ Score: 6.9
"Large language models (LLMs) are expanding from assisting scientific research and engineering to autonomously developing and improving AI systems, advancing AI for AI (AI4AI) as a pathway toward recursive self-improvement (RSI). Workflow-driven machine learning engineering (MLE) systems provide a pr..."
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🔬 RESEARCH
via Arxiv
👤 Séverin Baroudi, Yanis Labrak, Petr Motlicek et al.
📅 2026-10-16
⚡ Score: 6.8
"Qwen3-TTS reports state-of-the-art zero-shot voice cloning, but its technical report leaves open how the model should be conditioned, how it behaves outside read speech, and how it fails. We characterise its two cloning interfaces, in-context learning (ICL) and X-Vector, against Chatterbox, XTTS-v2..."
🔬 RESEARCH
via Arxiv
👤 Yuxing Chen, Zhisheng Zhang, Cheng Tang et al.
📅 2026-10-16
⚡ Score: 6.8
"Computational drug discovery requires agents to compose scientific operations and adapt to changing evidence and constraints. Here we introduce DrugHarness, an evolvable agent harness coupling composable scientific execution with conditional skill induction. Its environment integrates over 80 scient..."
🔬 RESEARCH
via Arxiv
👤 Leyang Shen, Yaxin Gong, Yang Zhang et al.
📅 2026-10-15
⚡ Score: 6.8
"Large language model (LLM)-based agents and multi-agent systems increasingly tackle complex tasks through long-horizon tool use and inter-agent collaboration. However, these systems are prone to deviating from the overall goal as execution unfolds, which wastes execution resources and leads to undes..."
🔬 RESEARCH
via Arxiv
👤 Andi Gu, Alek H. Kemeny, Susanne F. Yelin et al.
📅 2026-10-15
⚡ Score: 6.8
"Significant efforts are currently being directed toward the implementation of large-scale quantum information processors, but realizing useful quantum advantage also requires the development of efficient quantum algorithms. While for many practical problems the dominant resource costs are associated..."
🔬 RESEARCH
via Arxiv
👤 Jiaru Bai, Yuchi Zhao, Han Hao et al.
📅 2026-10-16
⚡ Score: 6.7
"Self-driving laboratories (SDLs) accelerate scientific discovery by automating experimental execution and optimization. AI agents can increasingly propose new experiments, but existing SDLs can only run the procedures they were built for. Adapting them to a new experiment still takes extensive manua..."
🔬 RESEARCH
via Arxiv
👤 Arnav Chavan, Kusha Sareen, Rishabh Tiwari et al.
📅 2026-10-15
⚡ Score: 6.7
"Large language models (LLMs) acquire new skills through fine-tuning, but it can destroy capabilities they already have: catastrophic forgetting remains a central obstacle to continual learning in LLMs. Recent works connect forgetting to how far, and along which directions, fine-tuning moves the weig..."
🔬 RESEARCH
via Arxiv
👤 Lewen Yan, Yanxu Zhu, Jie Zhang et al.
📅 2026-10-16
⚡ Score: 6.6
"Chain-of-Thought (CoT) monitoring offers actionable evidence for oversight AI systems, with the potential to enable early detection and intervention. However, existing approaches are focused on specific tasks, whereas the regulation of AI, particularly reasoning models, requires monitoring a broader..."
🔬 RESEARCH
via Arxiv
👤 Anikait Singh, Teresa Zhang, Yoonho Lee et al.
📅 2026-10-15
⚡ Score: 6.6
"Reasoning over long document contexts remains a challenge for large language models (LLMs). Standard retrieval methods are inherently reactive, bottlenecking agents with complex, cross-document reasoning at inference time, while precomputed structures like knowledge graphs often fall short because t..."
🛠️ SHOW HN
🎯 Compile-time optimization • Small model inference • Cost reduction at scale
💬 "Move expensive, nondeterministic part entirely to build time"
• "Infer once, repeat resulting logic forever is sustainable"
🔬 RESEARCH
via Arxiv
👤 Yipeng Gao, Ziyao Zeng, Jinfa Huang et al.
📅 2026-10-15
⚡ Score: 6.5
"We introduce 3DCodeVerse, a research ecosystem that enables coding agents to create editable and verifiable 3D content at scale. 3DCodeVerse comprises large-scale, high-quality datasets of executable 3D code, a coding harness for spatial reasoning and automated verification, and practical guidance f..."
🔬 RESEARCH
via Arxiv
👤 Yinuo Xu, Jadie Adams, Brian Hu et al.
📅 2026-10-16
⚡ Score: 6.1
"Personalizing a language model requires knowing what a person values, which stays largely consistent across tasks. Yet most methods either learn task-specific preferences or place the user's profile in the prompt, where models struggle to act on it. We introduce VISTA (Value-Informed Steering and Ta..."
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