January 2026

We present PCL-Reasoner-V1.5, a 32-billion-parameter large language model (LLM) for mathematical reasoning. The model is built upon Qwen2.5-32B and refined via supervised fine-tuning (SFT) followed by reinforcement learning (RL). A central innovation is our proposed offline RL method, which provides superior training stability and efficiency over standard online RL methods such as GRPO. Our model achieves state-of-the-art performance among models post-trained on Qwen2.5-32B, attaining average accuracies of 90.9% on AIME 2024 and 85.6% on AIME 2025. Our work […]

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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. ## AI Doesn’t Mean the End of Work for Us By @bernard [ 4 Min read ] I believe that AI’s impact and future pathways are overstated because human nature is ignored in such statements. Read More. Claude Code Launches Teleport Workflow: Start Anywhere, Continue […]

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Atlanta, GA, United States, January 20th, 2026/CyberNewsWire/–Airlock Digital, a leader in proactive application control and endpoint security, announced the release of The Total Economic Impact (TEI) of Airlock Digital, an independent study commissioned by Airlock Digital and conducted by Forrester Consulting. The study demonstrates a significant 224% return on investment (ROI) and a $3.8 million net present value (NPV) over three years for organizations adopting Airlock Digital’s allowlisting approach. These findings underline both the financial and security value of […]

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Symbolic Regression aims to automatically identify compact and interpretable mathematical expressions that model the functional relationship between input and output variables. Most existing search-based symbolic regression methods typically rely on the fitting error to inform the search process. However, in the vast expression space, numerous candidate expressions may exhibit similar error values while differing substantially in structure, leading to ambiguous search directions and hindering convergence to the underlying true function. To address this challenge, we propose a novel […]

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Federated Rank Learning (FRL) is a promising Federated Learning (FL) paradigm designed to be resilient against model poisoning attacks due to its discrete, ranking-based update mechanism. Unlike traditional FL methods that rely on model updates, FRL leverages discrete rankings as a communication parameter between clients and the server. This approach significantly reduces communication costs and limits an adversary’s ability to scale or optimize malicious updates in the continuous space, thereby enhancing its robustness. This makes FRL particularly appealing […]

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Learning Path Recommendation (LPR) aims to generate personalized sequences of learning items that maximize long-term learning effect while respecting pedagogical principles and operational constraints. Although large language models (LLMs) offer rich semantic understanding for free-form recommendation, applying them to long-horizon LPR is challenging due to (i) misalignment with pedagogical objectives such as the Zone of Proximal Development (ZPD) under sparse, delayed feedback, (ii) scarce and costly expert demonstrations, and (iii) multi-objective interactions among learning effect, difficulty scheduling, length […]

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Supervised deep learning models often achieve excellent performance within their training distribution but struggle to generalize beyond it. In cancer histopathology, for example, a convolutional neural network (CNN) may classify cancer severity accurately for cancer types represented in its training data, yet fail on related but unseen types. Although adenocarcinomas from different organs share morphological features that might support limited cross-domain generalization, addressing domain shift directly is necessary for robust performance. Domain adaptation offers a way to transfer […]

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A designer friend recently told me she spent three days trying to figure out why her company’s checkout flow made users confirm their email address twice. It seemed obviously redundant—just bad UX someone forgot to clean up. She asked the PM. She asked the engineer who built it. She even dug through old PRs looking for context. The best answer she got was: “There was something with the vendor API, but I don’t remember the details. Maybe check […]

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Around 2 years ago, our sales team was given a daunting task by our CEO – win an incremental 15 points of share in a market segment where we have less than 25% share today. The task seemed even more insurmountable given the fact that this customer segment had an entrenched competitor who had more than 50% share. As the strategy professional for the team, I was tasked with building the approach that the sales team could execute […]

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