digitado

Large Language Models (LLMs) have demonstrated impressive capabilities in a wide range of code generation tasks. However, generating code for certain domains remains challenging. One such domain is Computer-Aided Design (CAD) program, where the goal is to produce scripted parametric models that define object geometry for precise design and manufacturing applications. A key challenge in LLM-based CAD program generation is the limited geometric complexity of generated shapes compared to those found in real-world industrial designs. This shortfall is […]

Ver mais

Hey, everyone, is anyone from the sub going to ISBI this year? I have a paper accepted and will be giving an oral presentation. Would love to meet and connect in London for ISBI this year. submitted by /u/Marion-De [link] [comments]

Ver mais

The decentralized finance sector keeps expanding as tech giants including Google, OpenAI, Amazon, Meta, xAI, and Oracle signed a White House Ratepayer Protection Pledge to cover their AI data center energy costs. Tracking bitcoin hyper news is routine for Layer 2 watchers, but better opportunities exist during consolidation, and Pepeto with $7.5M raised and advancing exchange infrastructure offers returns that bitcoin hyper news cannot deliver. Tech Giants Sign White House Pledge to Cover AI Data Center Energy Costs […]

Ver mais

Hey guys, Any advice on functional regularization? Especially in physics applications, but general pointers are welcome too. I’m new to this and trying to understand how to regularize by controlling the function a model learns (its behavior), not just the parameters. Any good explanations, examples, or resources would be helpful! Also, I’m a bit confused about what the “original” functional regularization paper actually is, cause I’ve seen the term used in different contexts. Which paper is usually being […]

Ver mais

Cooperative multi-agent reinforcement learning (MARL) systems powered by large language models (LLMs) are frequently optimized via sparse terminal-only feedback. This shared signal entangles upstream decisions, obstructing accurate decision-level credit assignment. To address this trajectory-level diffusion, we introduce Contextual Counterfactual Credit Assignment (textbf{texttt{C3}}). Instead of distributing rewards across an entire episode, textbf{texttt{C3}} isolates the causal impact of individual messages by freezing the exact transcript-derived context, evaluating context-matched alternatives via fixed-continuation replay, and applying a leave-one-out (LOO) baseline. This localized […]

Ver mais

Natural Language Processing

Ver mais

In this paper, we study cooperative multi-agent reinforcement learning (MARL) where the joint reward exhibits submodularity, which is a natural property capturing diminishing marginal returns when adding agents to a team. Unlike standard MARL with additive rewards, submodular rewards model realistic scenarios where agent contributions overlap (e.g., multi-drone surveillance, collaborative exploration). We provide the first formal framework for this setting and develop algorithms with provable guarantees on sample efficiency and regret bound. For known dynamics, our greedy policy […]

Ver mais

Trump’s Department of War feud with Anthropic won’t impact other companies that are using Claude via Microsoft products.

Ver mais