Newest and Lowest Rated Papers

Isabelle Mahé, Marc Carrier, Didier Mayeur, Jean Chidiac, Eric Vicaut, Nicolas Falvo, Olivier Sanchez, Claire Grange, Manuel Monreal, Juan J. López-Núñez, Remedios Otero-Candelera, Grégoire Le Gal, Erik Yeo, Marc Righini, Helia Robert-Ebadi, Menno V. Huisman, Frederikus A. Klok, Peter Westerweel, Giancarlo Agnelli, Cecilia Becattini, Aristotelis Bamias, Kostas Syrigos, Sebastian Szmit, Adam Torbicki, Peter Verhamme, Anthony Maraveyas, Alexander T. Cohen, Cihan Ay, Céline Chapelle, Guy Meyer, Francis Couturaud, Patrick Mismetti, Philippe Girard, Laurent Bertoletti, Silvy Laporte

New England Journal of Medicine·2025·65 citations

No abstract available

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The Hedonistic Imperative: Objections

David Pearce

1995

Objections to the abolitionist project

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welcome to summitbridge, an extremely normal company – @nostalgebraist on Tumblr

Unknown Author

tumblr.com·2025

No abstract available

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Exploring the effects of prosocial and self-kindness interventions on mental health outcomes.

Maria Naclerio, Lee Lazar, Erica A Hornstein, Naomi I Eisenberger

Emotion (Washington, D.C.)·2025

A growing body of literature suggests that prosocial behavior, or behavior intended to help others, benefits well-being. However, modern society often places a greater emphasis on self-focused acts in the pursuit of well-being. To understand the effects of these differing forms of kindness (to others or the self), we conducted a 2-week intervention study of a community sample during the COVID-19 pandemic in 2020. Participants were randomly assigned to a prosocial (other-kindness), self-kindness, or control condition, and those in the active conditions were asked to perform three acts of kindness each week. Of those who completed the intervention ( = 777), we found that participants in the other-kindness (vs. control) group experienced significant decreases in depression, anxiety, and loneliness from pre- to postintervention, offering compelling evidence for the mental health benefits of prosocial behavior. Furthermore, we found that participants in the self-kindness (vs. control) group experienced significant decreases in depression, but no differences in anxiety and loneliness. While the self-kindness group reported experiencing more positive feelings during their acts of kindness, the other-kindness group felt more connected. Exploratory mediation analyses revealed that, for the prosocial group, the effect of condition on depression, anxiety, and loneliness was mediated by increases in feelings of social connection, whereas for the self-kindness group, the effect of condition on depression was mediated by increases in positive feelings. Overall, these findings reaffirm the benefits of prosocial behavior on well-being and suggest unique pathways to mental health benefits for these two forms of kindness. (PsycInfo Database Record (c) 2025 APA, all rights reserved).

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Physics of Language Models: Part 1, Learning Hierarchical Language Structures

Zeyuan Allen-Zhu, Yuanzhi Li

arXiv·2023

Transformer-based language models are effective but complex, and understanding their inner workings and reasoning mechanisms is a significant challenge. Previous research has primarily explored how these models handle simple tasks like name copying or selection, and we extend this by investigating how these models perform recursive language structure reasoning defined by context-free grammars (CFGs). We introduce a family of synthetic CFGs that produce hierarchical rules, capable of generating lengthy sentences (e.g., hundreds of tokens) that are locally ambiguous and require dynamic programming to parse. Despite this complexity, we demonstrate that generative models like GPT can accurately learn and reason over CFG-defined hierarchies and generate sentences based on it. We explore the model's internals, revealing that its hidden states precisely capture the structure of CFGs, and its attention patterns resemble the information passing in a dynamic programming algorithm. This paper also presents several corollaries, including showing why absolute positional embeddings is inferior to relative and rotary embeddings; uniform attention alone is surprisingly effective (motivating our follow-up work on Canon layers); encoder-only models (e.g., BERT, DeBERTa) struggle with deep structure reasoning on CFGs compared to autoregressive models (e.g., GPT); and injecting structural or syntactic noise into pretraining data markedly improves robustness to corrupted language prompts.

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Hindi Nangyari Dahil Wala sa Social Media: Interogasyon ng Kulturang New Media sa Pilipinas | Ateneo de Manila University Press

Ateneo de Manila University Press·2021

**This exciting collection gathers scholars and activists to exfoliate the complex layered dynamics of social media in the contemporary Philippines. From affective surges of desire, hopes and outrage in celebrity culture to the itinerant flows of dangerous (dis)information in the service of political manipulation and surveillance, Filipino social media culture is a panoramic and capacious vantage from which to mount a serious critical analysis and attain profound understanding of the country's travails and struggles.

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FastTD3: Simple, Fast, and Capable Reinforcement Learning for Humanoid Control

Younggyo Seo, Carmelo Sferrazza, Haoran Geng, Michal Nauman, Zhao-Heng Yin, Pieter Abbeel

arXiv·2025

Reinforcement learning (RL) has driven significant progress in robotics, but its complexity and long training times remain major bottlenecks. In this report, we introduce FastTD3, a simple, fast, and capable RL algorithm that significantly speeds up training for humanoid robots in popular suites such as HumanoidBench, IsaacLab, and MuJoCo Playground. Our recipe is remarkably simple: we train an off-policy TD3 agent with several modifications -- parallel simulation, large-batch updates, a distributional critic, and carefully tuned hyperparameters. FastTD3 solves a range of HumanoidBench tasks in under 3 hours on a single A100 GPU, while remaining stable during training. We also provide a lightweight and easy-to-use implementation of FastTD3 to accelerate RL research in robotics.

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Agentic Interactions

Alex Imas, Kevin Lee, Sanjog Misra

SSRN·2025

Do human differences persist and scale when decisions are delegated to AI agents? We study an experimental marketplace in which individuals author instructions for buyer-and seller-side agents that negotiate on their behalf. We compare these AI agentic interactions to standard human-to-human negotiations in the same setting. First, contrary to predictions of more homogenous outcomes, agentic interactions lead to, if anything, greater dispersion in outcomes compared to human-mediated interactions. Second, crossing agents across counterparties reveals systematic dispersion in outcomes that tracks the identity and characteristics of the human creators; who designs the agent matters as much as, and often more than, shared information or code. Canonical behavioral frictions reappear in agentic form: personality traits shape agent behavior and selection on principal characteristics yields sorting. Despite AI agents not having access to the human principal's characteristics, demographics such as gender and personality variables have substantial explanatory power for outcomes, in ways that are sometimes reversed from human-to-human interactions. Moreover, we uncover significant variation in "machine fluency"-the ability to instruct an AI agent to effectively align with one's objective function-that is predicted by principals' individual types, suggesting a new source of heterogeneity and inequality in economic outcomes. These results indicate that the agentic economy inherits, transforms, and may even amplify, human heterogeneity. Finally, we highlight a new type of information asymmetry in principal-agent relationships and the potential for specification hazard, and discuss broader implications for welfare, inequality, and market power in economies increasingly transacted through machines shaped by human intent.

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DLD Assessment: Start here

Difficulties in Translating Conjunctions in Arabic and English Languages: Study Based On Translation Students of South Eastern University Of Sri Lanka

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The Hedonistic Imperative: Objections

welcome to summitbridge, an extremely normal company – @nostalgebraist on Tumblr

Exploring the effects of prosocial and self-kindness interventions on mental health outcomes.

Physics of Language Models: Part 1, Learning Hierarchical Language Structures

PS 21 Wika, Panitikan, at Kultura sa Ilalim ng Batas Militar - Sentro ng Wikang Filipino

Hindi Nangyari Dahil Wala sa Social Media: Interogasyon ng Kulturang New Media sa Pilipinas | Ateneo de Manila University Press

FastTD3: Simple, Fast, and Capable Reinforcement Learning for Humanoid Control

Agentic Interactions