“To be honest, I'm almost developing a phobia of bananas. I created a prompt telling Gemini never to use the term "Nano banana," but it still used it.”

“"I kind of think of ads as like a last resort for us as a business model"”

“I just want to visualize my loss curve without paying w&b unacceptable pricing ($1 per gpu hour is absurd).”

“The award results show a strong preference for AI-related books.”

“ProUtt converts dialogue history into an intent tree and explicitly models intent reasoning trajectories by predicting the next plausible path from both exploitation and exploration perspectives.”

“Trip.com: "The company will actively cooperate with the regulatory authorities' investigation and fully implement regulatory requirements..."”

“Consumers can enable Personal Intelligence through a new option in the […]”

“I'm wondering when, or if, they will have access for people to create full videos with prompts to create anything they wish to see?”

“I have designed it for massively improved stability and audio quality over the original model. ... I have trained Soprano further to reduce these audio artifacts.”

“These modes allow AI to guide users through a step-by-step understanding by providing hints instead of directly providing answers.”

“"That's sad! We want the big limits back like before. Who knows - maybe Claude actually has better limits?"”

“SFT: Phase for teaching 'etiquette (format/inference rules)'; RL: Phase for teaching 'preferences (good/bad/safety)'”

“”

“”

“"Marvell和英特尔正在加快步伐，但Melius依然最看好英伟达和博通。"”

“These findings suggest that simply watching AI reasoning is not enough to catch hidden influences.”

“I think Gemini will win the overall AI general use from all companies due to the value proposition given.”

“"it's not about this, it's about that, "we faced this, we faced that and we faced this" and i hate when he makes comfort stuff that makes me sick."”

“"GPT5.2 cannot deliver any useful result, argues back, wastes your time. GEMINI 3 delivers with no drama like a pro."”

“Currently, I'm reading a Deep Learning by Ian Goodfellow et. al but the book focuses more on theory.. any suggestions for books that focuses more on implementation like having code examples except d2l.ai?”

“I am relatively new to coding, and only working on relatively small projects... Using the console/powershell etc for pretty much anything just intimidates me... So generally I just upload all my code to txt files, and then to a project, and this seems to work well enough. Was thinking of maybe setting up a GitHub instead and using that integration. But am I missing out? Should I bit the bullet and embrace Claude Code?”

“N/A”

“The model seems to be a step up in web design compared to previous Grok models and also it seems less lazy than previous Grok models.”

“The author mentions the need to correct and evaluate documents created by others, and the potential for evaluator preferences and experiences to influence the assessment, leading to inconsistencies.”

“There is no one correct way to use Claude Code: we intentionally build it in a way that you can use it, customize it and hack it however you like.”

“”

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

“Codex cloud is now called Codex web”

“The main contribution is a factor-$5$ distortion algorithm that requires only $O(k \log^2 k)$ queries.”

“Regret frequency is significantly linked to individual differences in decision-related orientations and status signaling, with a preference for online shopping further contributing to regret-prone consumption behaviors.”

“The paper introduces an explicit formulation of object arrangement preferences along four interpretable constructs: spatial practicality, habitual convenience, semantic coherence, and commonsense appropriateness.”

“The paper provides the first convergence guarantee for Optimistic Multiplicative Weights Update (OMWU) in NLHF, showing that it achieves last-iterate linear convergence after a burn-in phase whenever an NE with full support exists.”

“HiGR delivers consistent improvements in both offline evaluations and online deployment. Specifically, it outperforms state-of-the-art methods by over 10% in offline recommendation quality with a 5x inference speedup, while further achieving a 1.22% and 1.73% increase in Average Watch Time and Average Video Views in online A/B tests.”

“Cost Sensitivity and Behavioral Intention are the strongest positive predictors of adoption.”

“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.”

“The paper shows that selecting the most divisive proposals in a manner that satisfies certain seemingly mild normative requirements faces a number of fundamental difficulties.”

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

“CogRec leverages Soar as its core symbolic reasoning engine and leverages an LLM for knowledge initialization to populate its working memory with production rules.”

“The paper introduces evidence tokens for evidence grounding, which emphasize event-level visual semantic capture beyond the focus on timestamp representation.”

“The AHA framework, leveraging counterfactual hard negative mining, constructs a high-quality preference dataset that forces models to distinguish strict acoustic evidence from linguistically plausible fabrications.”

“The approach outperforms direct alignment methods based on standard A/B preference ranking or full contrastive rewrites, demonstrating that structured, revision-based supervision leads to more efficient and effective preference tuning.”

“The paper proposes verifiable off-chain computation (leveraging Verifiable Services, TEEs, and ZK proofs) as a framework to transcend these constraints while maintaining cryptoeconomic security.”

“”

“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.”

“C2PO leverages causal counterfactual signals to isolate bias-inducing features from valid reasoning paths, and employs a fairness-sensitive preference update mechanism to dynamically evaluate logit-level contributions and suppress shortcut features.”

“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.”

“The paper introduces the Keyword-Aware Top-$k$ Routes (KATR) query that provides a more flexible and comprehensive semantic to route planning that caters to various user's preferences including flexible POI visiting order, flexible travel distance budget, and personalized POI ratings.”

“Imagine never having to fumble with a charging cable again. That's the magic of a wireless charger.”