Identifying metabolic sites where cytochrome P450 enzymes metabolize small-molecule drugs is essential for drug discovery. Although existing computational approaches have been proposed for site-of-metabolism prediction, they typically ignore cytochrome P450 isoform identity or model isoforms independently, thereby failing to fully capture inherent cross-isoform metabolic patterns. In addition, prior evaluations often rely on top-k metrics, where false positive atoms may be included among the top predictions, underscoring the need for complementary metrics that more directly assess binary atom-level discrimination […]

Ver mais

How are you, hacker? 🪐Want to know what’s trending right now?: The Techbeat by HackerNoon has got you covered with fresh content from our trending stories of the day! Set email preference here. ## The End of CI/CD Pipelines: The Dawn of Agentic DevOps By @davidiyanu [ 10 Min read ] GitHub’s agent fixed my flaky test in 11 minutes. No human wrote code. But when it fails, instead of a stack trace, you get an outcome. Read […]

Ver mais

Hi everyone, I honestly feel like my mental health is not in a good place right now, and I just want to share this to see if anyone else has gone through something similar. If you’ve noticed, I’ve been posting quite a lot recently about my PhD thesis situation. I submitted my thesis a little over two months ago. Since that day, I’ve been in a constant state of anxiety waiting for the result. Every morning, the very […]

Ver mais

arXiv:2601.02379v1 Announce Type: new Abstract: Biological systems exhibit a continuous stream of movements, consisting of sequential segments, that allow them to perform complex tasks in a creative and versatile fashion. This observation has led researchers towards identifying elementary building blocks of motion known as movement primitives, which are well-suited for generating motor commands in autonomous systems, such as robots. In this survey, we provide an encyclopedic overview of movement primitive approaches and applications in chronological order. Concretely, we […]

Ver mais

I’ve been looking at per-task results on SWE-Bench Verified and noticed something that leaderboard averages hide: different models consistently solve different subsets of tasks. Even the top overall model on the leaderboard fails a non-trivial number of tasks that other models reliably solve, and the reverse is also true. This suggests strong task-level specialization rather than one model being strictly better. To test this, I built a Mixture-of-Models architecture, which is different from traditional routing that just defaults […]

Ver mais

Preference-Conditioned Policy Learning (PCPL) in Multi-Objective Reinforcement Learning (MORL) aims to approximate diverse Pareto-optimal solutions by conditioning policies on user-specified preferences over objectives. This enables a single model to flexibly adapt to arbitrary trade-offs at run-time by producing a policy on or near the Pareto front. However, existing benchmarks for PCPL are largely restricted to toy tasks and fixed environments, limiting their realism and scalability. To address this gap, we introduce GraphAllocBench, a flexible benchmark built on a […]

Ver mais

Researchers from Microsoft have unveiled a scanning method to identify poisoned models without knowing the trigger or intended outcome. Organisations integrating open-weight large language models (LLMs) face a specific supply chain vulnerability where distinct memory leaks and internal attention patterns expose hidden threats known as “sleeper agents”. These poisoned models contain backdoors that lie dormant during standard safety testing, but execute malicious behaviours – ranging from generating vulnerable code to hate speech – when a specific “trigger” phrase […]

Ver mais

arXiv:2601.16249v1 Announce Type: new Abstract: Learning DAG structures from purely observational data remains a long-standing challenge across scientific domains. An emerging line of research leverages the score of the data distribution to initially identify a topological order of the underlying DAG via leaf node detection and subsequently performs edge pruning for graph recovery. This paper extends the score matching framework for causal discovery, which is originally designated for continuous data, and introduces a novel leaf discriminant criterion based […]

Ver mais

Deterministic and probabilistic models of measured quantities, processes and fields in production process control systems, as well as physical and probabilistic measures, make it possible to form the measurement result and give it the properties of objectivity and reliability. The issue of improving and developing models and measures in measurement methodology plays an increasingly important role in achieving high measurement accuracy in control systems and the reliability of decision-making by expert systems in production processes. The measure is […]

Ver mais