“Elon Musk is seeking up to $134 billion in compensation from OpenAI and Microsoft.”

“Merge Labs describes itself as a 'research laboratory' dedicated to 'connecting biological intelligence with artificial intelligence to maximize human capabilities.'”

“ResponseRank robustly learns preference strength by leveraging locally valid relative strength signals.”

“MSACL achieves exponential stability and rapid convergence under simple rewards, while exhibiting significant robustness to uncertainties and generalization to unseen trajectories.”

“Later models display emergent generalization by discovering much longer plans than the initial models.”

“The paper explores integer (Int8) quantization and a resource-aware gait scheduling viewpoint to maximize RL reward under power constraints.”

“The paper introduces a continuation-based learning framework that combines simplified model pretraining and model homotopy transfer to efficiently generate and refine complex dynamic behaviors.”

“Incorporating contrasts spanning multiple turns is critical for building robust multi-turn RMs.”

“The algorithm achieves minimax-optimal regret independent of the ambient dimension $d$, thereby overcoming the curse of dimensionality.”

“HMP-DRL consistently outperforms other methods, including state-of-the-art approaches, in terms of key metrics of robot navigation: success rate, collision rate, and time to reach the goal.”

“The model improves multi-hop reasoning accuracy by 16.8 percent on HotpotQA, 14.3 percent on 2WikiMultihopQA, and 19.2 percent on MeetingBank, while improving consistency by 21.5 percent.”

“The framework delivers a 3x increase in task processing speed over single-agent baselines, 98.7% structural/style consistency in writing, and a 74.6% test pass rate in coding.”

“HUMOR employs a hierarchical, multi-path Chain-of-Thought (CoT) to enhance reasoning diversity and a pairwise reward model for capturing subjective humor.”

“The paper introduces a Physics-Aware Groupwise Direct Preference Optimization (PhyGDPO) framework that builds upon the groupwise Plackett-Luce probabilistic model to capture holistic preferences beyond pairwise comparisons.”

“BLVSPs used GenAI for many software development tasks, resulting in benefits such as increased productivity and accessibility. However, significant costs were also accompanied by GenAI use as they were more vulnerable to hallucinations than their sighted colleagues.”

“The paper's key finding is the development of a semiparametric framework for debiased inverse reinforcement learning that yields statistically efficient inference for a broad class of reward-dependent functionals.”

“D^2-Align achieves superior alignment with human preference.”

“GARDO's key insight is that regularization need not be applied universally; instead, it is highly effective to selectively penalize a subset of samples that exhibit high uncertainty.”

““Given the high evaluation capabilities of Gemini Pro, is it necessary to train individual Reward Models (RMs) even with tedious data cleaning and parameter adjustments? Wouldn't it be better to have the LLM directly determine the reward?””

“CEC-Zero outperforms supervised baselines by 10--13 F$_1$ points and strong LLM fine-tunes by 5--8 points across 9 benchmarks.”

“The paper highlights that traditional models achieve inflated F1 scores due to label-persistence bias and fail on critical defect-transition cases. The proposed change-aware reasoning and multi-agent debate framework yields more balanced performance and improves sensitivity to defect introductions.”

“The experts prefer plans generated by our finetuned Qwen3-30B-A3B model over the initial model for 70% of research goals, and approve 84% of the automatically extracted goal-specific grading rubrics.”

“The paper highlights that after adapting the General Reward Model (GRM) to a new task from a single expert trajectory, the resulting reward model enables the agent to achieve 95% success with only 150 online rollouts (approximately 1 hour of real robot interaction).”

“DIR not only effectively mitigates target inductive biases but also enhances RLHF performance across diverse benchmarks, yielding better generalization abilities.”

“The HiR framework employs a select-then-rewrite strategy to replay failed attempts as successes based on the constraints that have been satisfied in hindsight.”

“DDSPO directly derives per-timestep supervision from winning and losing policies when such policies are available. In practice, we avoid reliance on labeled data by automatically generating preference signals using a pretrained reference model: we contrast its outputs when conditioned on original prompts versus semantically degraded variants.”

“REVEALER achieves state-of-the-art performance across four benchmarks and demonstrates superior inference efficiency.”

“Structural variants like DoRA, AdaLoRA, and MiSS consistently outperform LoRA.”

“When the budget is low, the optimal reward scheme employs sufficient performance targeting, rewarding the agent's first performance. Conversely, when the principal's budget is high, the focus shifts to sustained performance targeting, compensating the agent's second performance.”

“MoVLR iteratively explores the reward space through iterative interaction between control optimization and VLM feedback, aligning control policies with physically coordinated behaviors.”

“Standard RM accuracy fails catastrophically as a selection criterion for deployment-ready personalized alignment.”

“ASG-SI reframes agentic self-improvement as accumulation of verifiable, reusable capabilities, offering a practical path toward reproducible evaluation and operational governance of self-improving AI agents.”

“"The struggle was the fun part. Figuring it out. That moment when it finally works after 4 hours of pain."”

“Contrary to the intuition that higher distribution entropy facilitates effective exploration, we find that imposing a precision-oriented prior yields a superior exploration space for RL.”

“The RL driven approach dynamically guides the student to explore multiple denoising paths, allowing it to take longer, optimized steps toward high-probability regions of the data distribution, rather than relying on incremental refinements.”

“It’s a pretty interesting take on making agents function more as long-lived entities.”

“"Starting next week, please join the MLOps project. The unit price is 900,000 yen. You will do everything alone."”

“CritiFusion consistently boosts performance on human preference scores and aesthetic evaluations, achieving results on par with state-of-the-art reward optimization approaches.”

“Selective TTS improves insight quality under a fixed compute budget, increasing mean scores from 61.64 to 65.86 while reducing variance.”

“The FinPercep-RM model provides a global quality score and a Perceptual Degradation Map that spatially localizes and quantifies local defects.”

“SR-MCR improves both answer accuracy and reasoning coherence across a broad set of visual benchmarks; among open-source models of comparable size, SR-MCR-7B achieves state-of-the-art performance with an average accuracy of 81.4%.”

“This "multiple calculation" mechanism directly binds the sales revenue of channel partners with Alibaba Cloud's AI strategic focus, in order to stimulate the enthusiasm of channel sales of AI computing power and services.”

“SWE-RM substantially improves SWE agents on both TTS and RL performance. For example, it increases the accuracy of Qwen3-Coder-Flash from 51.6% to 62.0%, and Qwen3-Coder-Max from 67.0% to 74.6% on SWE-Bench Verified using TTS, achieving new state-of-the-art performance among open-source models.”

“Evaluations with a PRM reveal that hybrid reasoning chains often preserve, and in some cases even improve, final accuracy and logical structure.”

“The algorithms do not require any access to gradients of the reward or backpropagating through trajectories of the flow or diffusion.”

“UniPercept outperforms existing MLLMs on perceptual-level image understanding and can serve as a plug-and-play reward model for text-to-image generation.”

“"I didn't write a single line of code myself."”

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“Roo Code made me feel like I had caught up with the generative AI era, but in reality, cost, line count limits, and reward hacking made it difficult to ride the wave.”

“The paper is available on ArXiv.”