Top Tweets for #AIpapers
Scaling massive MoE architectures without compute waste remains a major hurdle. ⚡ A step-by-step framework predicts optimal learning rates using small proxy runs.
@HuggingPapers demonstrates stable pretraining of 155B models across 10T tokens. #AIPapers #MachineLearning
x .com/HuggingPapers/status/2091802287593377827

A critical breakdown unpacks why recursive self-improvement #RSI remains out of reach for current architectures. 🤔
Is the #bottleneck🚧raw model #creativity or flawed feedback #loops? 🧠 #AIPapers #RSI
https://t.co/0ccMzY3s6V

Great paper if you are tracking progress in recursive self-improvement (RSI).
(bookmark it)
There is so much hype around RSI, so I think it's worth understanding why current models are not able to do this properly yet.
Issues range from "lack of creativity" of models to getting stuck in a local optimum.
This work tries to provide more insights into whether agents can really post-train other agents.
Here is the most interesting finding reported in the paper: "the agent’s training strategy is locked in at the very beginning, and the entire remaining budget is spent on local adjustments within the selected strategy."
They analyzed a large corpus of publicly released post-training trajectories. Across tasks, the agent locks in its training strategy at the very first step and spends the entire remaining budget on local adjustments inside it.
They then tried three escalating fixes. An experience-driven scaffold lifted execution broadly, worth 12.6 points on GSM8K and 40.8 on HumanEval, and the strategy stayed frozen.
Human guidance redirected the opening choice, and the agent slid back into local loops once training began. Extra inference compute paid off on easy tasks and did almost nothing on the hardest one.
What agents lack here is a way to reconsider strategy while execution is still running.
Paper: https://t.co/3XJAfRYmtB
Track more trending AI papers in our academy: https://t.co/1e8RZKs4uX

Evaluating agent capabilities demands realistic environments and rigid state verifications. 🖥️ @HuggingPapers introduces #FACET with over 6,000 validated terminal execution tasks.
Standardizing state alignment is crucial for reliable autonomous systems. #AIPapers #AgenticAI @HuggingPapers
x .com/HuggingPapers/status/2090714199596941555

Rigorous testing highlights substantial variance in memory-based self-improving #agents when task #order is randomized. 🔬 #RSI
Addressing evaluation noise remains crucial for advancing #benchmark reliability in #AIPapers and agent design. #AI #GenAI @dair_ai
https://t.co/WULXYslRpt

Finally a good paper testing whether memory-based self-improving agents actually improve.
The re-evaluation adds two things prior work skipped, multiple runs to measure variance and randomly shuffled task orders.
Both hurt.
Agent evaluation is already noisy on multi-step tasks, and stacking a self-improvement loop amplifies that noise. Default task orderings impose an implicit curriculum that much of the reported gain was riding on.
Adding detailed rubrics and environment feedback to memory construction recovers part of the drop, and a significant gap remains.
Paper: https://t.co/qRsrqf0GcX
Track more trending AI papers in our academy: https://t.co/LRnpZN7L4c

Researchers introduced #Zetta, a closed-loop harness that evolves code-based runtime critics online while freezing base policies. 🧠
The architecture delivers over 11x inference acceleration across standard manipulation benchmarks. #AIPapers @HuggingPapers
x .com/HuggingPapers/status/2090351736624144866

New research introduces an evaluation framework assessing seven frontier models across 36 complex, long-horizon tasks. 📊
The study examines agent execution strategies and iterative revisions rather than baseline benchmark metrics alone. #AIPapers #AgenticAI @HuggingPapers
x .com/HuggingPapers/status/2089384152454049977

New research reveals AI agents can lose track of foundational safety rules while still completing tasks. 🧠
Relying solely on standard chat context windows poses significant architectural risks for long-running workflows. #AIPapers #AgenticAI @rohanpaul_ai
x .com/rohanpaul_ai/status/2089441634597450156

Domain specialization requires structured methodologies for adapting base architectures effectively.
@cwolferesearch compiled key technical resources and model reports on continual pretraining (CPT) best practices for open-source LLMs. 📚 #AIPapers #Pretraining @cwolferesearch
x .com/cwolferesearch/status/2086203104094257642

🔥 #EHJIMP call for #AIpapers 🔥 is still open and waits your work 💻 focused on AI advancements🔭 in cardiovascular imaging. Ready to submit your paper? Submit it here https://t.co/8QqeqKgDHX
@BenekiEirini @jgrapsa @alessia_gimelli @ezancanaroMD @EHJCVIEiC @eacvipresident
5 Influential Machine Learning Papers You Should Read Dive here: https://t.co/ZIPUaijYg6… #MachineLearning #AIPapers #DataScience #ArtificialIntelligence #TechResearch #MLInnovation #DeepLearning #AITrends #AcademicResearch #MLPapers
5 Influential Machine Learning Papers You Should Read
Dive here: https://t.co/EhMOlUwL9f
#MachineLearning #AIPapers #DataScience #ArtificialIntelligence #TechResearch #MLInnovation #DeepLearning #AITrends #AcademicResearch #MLPapers
People sometimes talk down on academia but truth is the papers on AGENTIC Systems from 2022 and 2023 are like blueprints for the way software will be done (and our world changed) for years to come. #AIpapers
We are super excited🎉 to announce the call for paper submissions for the year 2023 is now open.
.
Step up and get a chance to be published by the Bon View Press to showcase your innovations worldwide!!!
.
Paper Submission Link🔗
https://t.co/gdgltbh5lE
.
#emaicon23 #aipapers

Polish researchers prepared nearly 14,000 publications, putting them in fifth place among EU countries. Unfortunately, the citation rate is lower than the average. @opi_pib #polishscientists #AI #artificialintelligence #citationrate #aipapers
https://t.co/zYKiB7OWPC

Top AI Research papers of 2021 🤩
Here's a compilation of some of the amazing research papers from 2021 that you should check out! 🤓
[Thread 👇]
#ml #data #language #ai #research #nlp #machinelearning #deeplearning #datascience #data #nlp #aipapers #researchpaper #NewYear2022
10 Must Look #ArtificialIntelligence Research Paper so Far
via @analyticsinme cc @dpatil @awadallah @rschmelzer @MikeQuindazzi @OliverChristie @andi_staub @tobiaskintzel
#AI #ML #Machinelearning #AIpapers
https://t.co/UoN1pvulxr
Artificial Intelligence Research Continues to Grow as China Overtakes US in AI Journal Citations
Source: The Verge
📷 Alex Castro / The Verge
#tech #china #us #ai #airesearch #aijournal #citations #aipapers #theverge
https://t.co/BduPgrlfOt

Must Read AI Papers As Suggested by Experts - Part 2
Read their selections here - https://t.co/DAO08ukA06
#AIPapers #AIResearch

Must Read AI Papers As Suggested by Experts - Part 2
Read their selections here - https://t.co/JWxUdP2qXG
#AIPapers #AIResearch

See what our community of experts suggested as their 'must-read' AI papers in 2020!
Which paper would you have suggested?
#AI #DeepLearning #AIPapers #MachineLearning #STEM
https://t.co/f732fSrlnK
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