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@hex@kolektiva.social
2026-02-28 10:20:01

As salty as I am about it, there's also another way to think about this. For anyone who still has connections to folks on the right (which is perhaps unlikely for anyone on this server, I digress), the cult that has consumed them thrives on isolation and grievance.
The words "you were right" have the potential to cut through the programming and open up an opportunity for reconnection. The modern conspiratorial cult of the Right has been built partially around people who were told they were wrong or were crazy. In the vast majority of cases, they were wrong and even when they were right they completely misunderstood why, but we'll skip that for now. Liberals making fun of them (even the times when they definitely earned it) has pushed them further and further into their ideological hole.
The thing about those words, "you were right," in this context is that the way they offer reconnection also requires them to take one little step of betraying their ideology to accept them. So they must choose between maintaining allegiance to a pedophile or finally getting to feel superior after years of living in an illusion of persecution.
Under the ideology of the Right, admitting one is wrong is a weakness. It is admitting defeat. They have to "own the libs" by saying things, things that they know aren't true, in order to feel dominant. But these things are often so absurd that they end up being made fun of, feeling even more weak and pathetic, reinforcing their fear and alienation.
Offering what they're looking for can offer a way out, but only if they're willing to start to recognize the thing they've supported for what it is.
And they were right about some things. They were right that Bill Gates was a terrible person. I've had plenty of liberals defend him based on his philanthropy washing, but he's awful and always has been. The Epstein links make that blatant. They intuitively recognized him and didn't trust him, even if they were wildly off base about *how and why* he shouldn't be trusted... Even if their correct mistrust was leveraged into one of the most destructive conspiracy theories ever (vaccine denial and COVID vaccine avoidance).
They were right about Bill Clinton. He was always shady as fuck. Sure, the people who attacked him at the time turned out to be even more shady but that's not the point right now. He was connected to Epstein and that was always creepy as fuck.
And the Epstein thing was an open secret that liberals ignored for a long time. It was seen as some weird thing that right wing nutjobs believed about the Clintons. But it was true. Not all of it, and there has always been an antisemitic element to the right wing interpretation or Epstein stuff, but his whole pedophile conspiracy was always kind of real.
The whole "Illuminati"/deep state thing is a vast oversimplification, an attempt to make comprehensible an incredibly complex set of interlocking and emergent behaviors. But Epstein did very much want to remake the world, to create a new world order, and he absolutely played a part in it.
The Right wing nutjobs talked about global authoritarianism, Blackhawks flying over American cities, masked men with guns disarming and executing legal gun owners in the streets. That's all happening right now.
The "FEMA concentration camps" are not actually that far off. ICE and FEMA are sister agencies, both under DHS. I'd be more than happy to call that one "close enough" in order to hear some MAGA admit that ICE is, in fact, building concentration camps.
There was always a huge millennialist element to these things. They tended to be connected to "the antichrist." It was absurd, especially for me as someone who no longer identifies as a Christian. But I'll even acquiess that to a degree. The "the number of the Beast" is 666. That's just the sum of the Hebrew spelling of "Nero." Revelations focuses a lot on Nero coming back to life after his death. His death that involved a head wound, thus the line from Revelation 13:3:
> And I saw one of his heads as if it had been mortally wounded, and his deadly wound was healed. And all the world marveled and followed the beast.
The parallels between Trump and Nero are easy to draw, and Trump's ear wound feels pretty on-the-nose for this. I don't believe in "prophecy" in this way. I think that there are patterns, and useful patterns can become encoded in beleif systems. But I will, again, happily call this one "close enough" for anyone on that side willing to also acknowledge it. I'm happy to meet on that common ground, because anyone who accepts it must recognize that their duty is to fight against it.
A lot of these correct nuggets are embedded in a framework of religious extremism and antisemitism. The vast majority of the beliefs holding these together are wildly wrong and incredibly toxic. But by giving some room to feel validated, listened to, understood, can give some room to admit things that were wrong.
Cult de-programming starts with an opening. People have to talk through their own thoughts, hear their own inconsistencies. Guiding questions can help them untangle these things for themselves. And it all starts by having enough room to feel safe, to not feel cornered, to not feel stupid. Admitting mistakes means being vulnerable, and the MAGA cult is built on fear. It's built on exploiting vulnerability and locking it away.
De-programming takes a long time. It's not easy. It takes patience. But every person who comes out does so with a powerful perspective, a deep understanding, that can be turned back against it. The best people at getting people out of cults are former members. Some of the most dedicated antifa are former fascists who understood their mistakes and dedicate their lives to fixing them.

@frankel@mastodon.top
2026-03-01 09:21:40

Code Mode: give #agents an entire #API in 1,000 #tokens

Code Mode: give agents an entire API in 1,000 tokens
The Cloudflare API has over 2,500 endpoints. Exposing each one as an MCP tool would consume over 2 million tokens. With Code Mode, we collapsed all of it into two tools and roughly 1,000 tokens of context.

@arXiv_csCL_bot@mastoxiv.page
2026-03-31 11:12:28

Replaced article(s) found for cs.CL. arxiv.org/list/cs.CL/new
[1/5]:
- Beyond In-Distribution Success: Scaling Curves of CoT Granularity for Language Model Generalization
Ru Wang, Wei Huang, Selena Song, Haoyu Zhang, Qian Niu, Yusuke Iwasawa, Yutaka Matsuo, Jiaxian Guo
arxiv.org/abs/2502.18273 mastoxiv.page/@arXiv_csCL_bot/
- Benchmarking NLP-supported Language Sample Analysis for Swiss Children's Speech
Anja Ryser, Yingqiang Gao, Sarah Ebling
arxiv.org/abs/2504.00780 mastoxiv.page/@arXiv_csCL_bot/
- Cultural Biases of Large Language Models and Humans in Historical Interpretation
Fabio Celli, Georgios Spathulas
arxiv.org/abs/2504.02572 mastoxiv.page/@arXiv_csCL_bot/
- BRIDGE: Benchmarking Large Language Models for Understanding Real-world Clinical Practice Text
Jiageng Wu, et al.
arxiv.org/abs/2504.19467 mastoxiv.page/@arXiv_csCL_bot/
- Understanding the Anchoring Effect of LLM with Synthetic Data: Existence, Mechanism, and Potentia...
Yiming Huang, Biquan Bie, Zuqiu Na, Weilin Ruan, Songxin Lei, Yutao Yue, Xinlei He
arxiv.org/abs/2505.15392 mastoxiv.page/@arXiv_csCL_bot/
- Just as Humans Need Vaccines, So Do Models: Model Immunization to Combat Falsehoods
Raza, Qureshi, Farooq, Lotif, Chadha, Pandya, Emmanouilidis
arxiv.org/abs/2505.17870 mastoxiv.page/@arXiv_csCL_bot/
- LingoLoop Attack: Trapping MLLMs via Linguistic Context and State Entrapment into Endless Loops
Fu, Jiang, Hong, Li, Guo, Yang, Chen, Zhang
arxiv.org/abs/2506.14493 mastoxiv.page/@arXiv_csCL_bot/
- GHTM: A Graph-based Hybrid Topic Modeling Approach with a Benchmark Dataset for the Low-Resource ...
Farhana Haque, Md. Abdur Rahman, Sumon Ahmed
arxiv.org/abs/2508.00605 mastoxiv.page/@arXiv_csCL_bot/
- Link Prediction for Event Logs in the Process Industry
Anastasia Zhukova, Thomas Walton, Christian E. Lobm\"uller, Bela Gipp
arxiv.org/abs/2508.09096 mastoxiv.page/@arXiv_csCL_bot/
- AirQA: A Comprehensive QA Dataset for AI Research with Instance-Level Evaluation
Huang, Cao, Zhang, Kang, Wang, Wang, Luo, Zheng, Qian, Chen, Yu
arxiv.org/abs/2509.16952 mastoxiv.page/@arXiv_csCL_bot/
- Multi-View Attention Multiple-Instance Learning Enhanced by LLM Reasoning for Cognitive Distortio...
Jun Seo Kim, Hyemi Kim, Woo Joo Oh, Hongjin Cho, Hochul Lee, Hye Hyeon Kim
arxiv.org/abs/2509.17292 mastoxiv.page/@arXiv_csCL_bot/
- Dual-Space Smoothness for Robust and Balanced LLM Unlearning
Han Yan, Zheyuan Liu, Meng Jiang
arxiv.org/abs/2509.23362 mastoxiv.page/@arXiv_csCL_bot/
- The Rise of AfricaNLP: Contributions, Contributors, Community Impact, and Bibliometric Analysis
Tadesse Destaw Belay, et al.
arxiv.org/abs/2509.25477 mastoxiv.page/@arXiv_csCL_bot/
- Open ASR Leaderboard: Towards Reproducible and Transparent Multilingual and Long-Form Speech Reco...
Srivastav, Zheng, Bezzam, Le Bihan, Koluguri, \.Zelasko, Majumdar, Moumen, Gandhi
arxiv.org/abs/2510.06961 mastoxiv.page/@arXiv_csCL_bot/
- Neuron-Level Analysis of Cultural Understanding in Large Language Models
Taisei Yamamoto, Ryoma Kumon, Danushka Bollegala, Hitomi Yanaka
arxiv.org/abs/2510.08284 mastoxiv.page/@arXiv_csCL_bot/
- CLMN: Concept based Language Models via Neural Symbolic Reasoning
Yibo Yang
arxiv.org/abs/2510.10063 mastoxiv.page/@arXiv_csCL_bot/
- Schema for In-Context Learning
Chen, Chen, Wang, Leong, Fung, Bernales, Aspuru-Guzik
arxiv.org/abs/2510.13905 mastoxiv.page/@arXiv_csCL_bot/
- Evaluating Latent Knowledge of Public Tabular Datasets in Large Language Models
Matteo Silvestri, Fabiano Veglianti, Flavio Giorgi, Fabrizio Silvestri, Gabriele Tolomei
arxiv.org/abs/2510.20351 mastoxiv.page/@arXiv_csCL_bot/
- LuxIT: A Luxembourgish Instruction Tuning Dataset from Monolingual Seed Data
Julian Valline, Cedric Lothritz, Siwen Guo, Jordi Cabot
arxiv.org/abs/2510.24434 mastoxiv.page/@arXiv_csCL_bot/
- Surfacing Subtle Stereotypes: A Multilingual, Debate-Oriented Evaluation of Modern LLMs
Muhammed Saeed, Muhammad Abdul-mageed, Shady Shehata
arxiv.org/abs/2511.01187 mastoxiv.page/@arXiv_csCL_bot/
toXiv_bot_toot

@mszll@datasci.social
2026-03-02 07:26:34

URBAN-SPIN: A street-level bikeability index to inform design implementations in historical city centres
arxiv.org/abs/2602.10124

URBAN-SPIN: A street-level bikeability index to inform design implementations in historical city centres
Cycling is reported by an average of 35\% of adults at least once per week across 28 countries, and as vulnerable road users directly exposed to their surroundings, cyclists experience the street at an intensity unmatched by other modes. Yet the street-level features that shape this experience remain under-analysed, particularly in historical urban contexts where spatial constraints rule out large-scale infrastructural change and where typological context is often overlooked. This study develop…

@rmdes@mstdn.social
2026-02-01 17:45:21

About “auto compaction” and why you’re better off turning it off and controlling when it happens intentionally !
❤️ decodeclaude.com/compaction-de

Inside Claude Code's Compaction System — Decode Claude
How Claude Code manages its 200k token context window — reverse engineered from the npm tarball.

@arXiv_csCL_bot@mastoxiv.page
2026-03-31 10:40:54

Crosslisted article(s) found for cs.CL. arxiv.org/list/cs.CL/new
[1/2]:
- Bridge-RAG: An Abstract Bridge Tree Based Retrieval Augmented Generation Algorithm With Cuckoo Fi...
Li, Liu, Zong, Tao, Dai, Ren, Liu, Jiang, Yang
arxiv.org/abs/2603.26668 mastoxiv.page/@arXiv_csIR_bot/
- SRAG: RAG with Structured Data Improves Vector Retrieval
Shalin Shah, Srikanth Ryali, Ramasubbu Venkatesh
arxiv.org/abs/2603.26670 mastoxiv.page/@arXiv_csIR_bot/
- LITTA: Late-Interaction and Test-Time Alignment for Visually-Grounded Multimodal Retrieval
Seonok Kim
arxiv.org/abs/2603.26683 mastoxiv.page/@arXiv_csIR_bot/
- Agentic AI for Human Resources: LLM-Driven Candidate Assessment
Yuksel, Anees, Elneima, Hewavitharana, Al-Badrashiny, Sawaf
arxiv.org/abs/2603.26710 mastoxiv.page/@arXiv_csIR_bot/
- SEAR: Schema-Based Evaluation and Routing for LLM Gateways
Zecheng Zhang, Han Zheng, Yue Xu
arxiv.org/abs/2603.26728 mastoxiv.page/@arXiv_csDB_bot/
- SleepVLM: Explainable and Rule-Grounded Sleep Staging via a Vision-Language Model
Guifeng Deng, Pan Wang, Jiquan Wang, Shuying Rao, Junyi Xie, Wanjun Guo, Tao Li, Haiteng Jiang
arxiv.org/abs/2603.26738 mastoxiv.page/@arXiv_csCV_bot/
- Aesthetic Assessment of Chinese Handwritings Based on Vision Language Models
Chen Zheng, Yuxuan Lai, Haoyang Lu, Wentao Ma, Jitao Yang, Jian Wang
arxiv.org/abs/2603.26768 mastoxiv.page/@arXiv_csCV_bot/
- Learning to Select Visual In-Context Demonstrations
Eugene Lee, Yu-Chi Lin, Jiajie Diao
arxiv.org/abs/2603.26775 mastoxiv.page/@arXiv_csLG_bot/
- CRISP: Characterizing Relative Impact of Scholarly Publications
Hannah Collison, Benjamin Van Durme, Daniel Khashabi
arxiv.org/abs/2603.26791 mastoxiv.page/@arXiv_csDL_bot/
- GroupRAG: Cognitively Inspired Group-Aware Retrieval and Reasoning via Knowledge-Driven Problem S...
Xinyi Duan, Yuanrong Tang, Jiangtao Gong
arxiv.org/abs/2603.26807 mastoxiv.page/@arXiv_csIR_bot/
- In your own words: computationally identifying interpretable themes in free-text survey data
Jenny S Wang, Aliya Saperstein, Emma Pierson
arxiv.org/abs/2603.26930 mastoxiv.page/@arXiv_csCY_bot/
- Multilingual Stutter Event Detection for English, German, and Mandarin Speech
Felix Haas, Sebastian P. Bayerl
arxiv.org/abs/2603.26939 mastoxiv.page/@arXiv_csSD_bot/
- FormalProofBench: Can Models Write Graduate Level Math Proofs That Are Formally Verified?
Ravi, Ying, Nesterov, Krishnan, Uskuplu, Xia, Aswedige, Nashold
arxiv.org/abs/2603.26996 mastoxiv.page/@arXiv_csAI_bot/
- PHONOS: PHOnetic Neutralization for Online Streaming Applications
Waris Quamer, Mu-Ruei Tseng, Ghady Nasrallah, Ricardo Gutierrez-Osuna
arxiv.org/abs/2603.27001 mastoxiv.page/@arXiv_eessAS_bo
- ChartNet: A Million-Scale, High-Quality Multimodal Dataset for Robust Chart Understanding
Jovana Kondic, et al.
arxiv.org/abs/2603.27064 mastoxiv.page/@arXiv_csCV_bot/
- daVinci-LLM:Towards the Science of Pretraining
Qin, Liu, Mi, Xie, Huang, Si, Lu, Feng, Wu, Liu, Luo, Hou, Guo, Qiao, Liu
arxiv.org/abs/2603.27164 mastoxiv.page/@arXiv_csAI_bot/
- LightMover: Generative Light Movement with Color and Intensity Controls
Zhou, Wang, Kim, Shu, Yu, Hold-Geoffroy, Chaturvedi, Wu, Lin, Cohen
arxiv.org/abs/2603.27209 mastoxiv.page/@arXiv_csCV_bot/
- Self-evolving AI agents for protein discovery and directed evolution
Tan, Zhang, Li, Yu, Zhong, Zhou, Dong, Hong
arxiv.org/abs/2603.27303 mastoxiv.page/@arXiv_csAI_bot/
- Inference-Time Structural Reasoning for Compositional Vision-Language Understanding
Amartya Bhattacharya
arxiv.org/abs/2603.27349 mastoxiv.page/@arXiv_csCV_bot/
- LLM Readiness Harness: Evaluation, Observability, and CI Gates for LLM/RAG Applications
Alexandre Cristov\~ao Maiorano
arxiv.org/abs/2603.27355 mastoxiv.page/@arXiv_csAI_bot/
- Heterogeneous Debate Engine: Identity-Grounded Cognitive Architecture for Resilient LLM-Based Eth...
Jakub Mas{\l}owski, Jaros{\l}aw A. Chudziak
arxiv.org/abs/2603.27404 mastoxiv.page/@arXiv_csAI_bot/
toXiv_bot_toot

@arXiv_csLG_bot@mastoxiv.page
2026-02-25 16:08:18

Replaced article(s) found for cs.LG. arxiv.org/list/cs.LG/new
[5/6]:
- Watermarking Degrades Alignment in Language Models: Analysis and Mitigation
Apurv Verma, NhatHai Phan, Shubhendu Trivedi
arxiv.org/abs/2506.04462 mastoxiv.page/@arXiv_csCL_bot/
- Sensory-Motor Control with Large Language Models via Iterative Policy Refinement
J\^onata Tyska Carvalho, Stefano Nolfi
arxiv.org/abs/2506.04867 mastoxiv.page/@arXiv_csAI_bot/
- ICE-ID: A Novel Historical Census Dataset for Longitudinal Identity Resolution
de Carvalho, Popov, Kaatee, Correia, Th\'orisson, Li, Bj\"ornsson, Sigur{\dh}arson, Dibangoye
arxiv.org/abs/2506.13792 mastoxiv.page/@arXiv_csAI_bot/
- Feedback-driven recurrent quantum neural network universality
Lukas Gonon, Rodrigo Mart\'inez-Pe\~na, Juan-Pablo Ortega
arxiv.org/abs/2506.16332 mastoxiv.page/@arXiv_quantph_b
- Programming by Backprop: An Instruction is Worth 100 Examples When Finetuning LLMs
Cook, Sapora, Ahmadian, Khan, Rocktaschel, Foerster, Ruis
arxiv.org/abs/2506.18777 mastoxiv.page/@arXiv_csAI_bot/
- Stochastic Quantum Spiking Neural Networks with Quantum Memory and Local Learning
Jiechen Chen, Bipin Rajendran, Osvaldo Simeone
arxiv.org/abs/2506.21324 mastoxiv.page/@arXiv_csNE_bot/
- Enjoying Non-linearity in Multinomial Logistic Bandits: A Minimax-Optimal Algorithm
Pierre Boudart (SIERRA), Pierre Gaillard (Thoth), Alessandro Rudi (PSL, DI-ENS, Inria)
arxiv.org/abs/2507.05306 mastoxiv.page/@arXiv_statML_bo
- Characterizing State Space Model and Hybrid Language Model Performance with Long Context
Saptarshi Mitra, Rachid Karami, Haocheng Xu, Sitao Huang, Hyoukjun Kwon
arxiv.org/abs/2507.12442 mastoxiv.page/@arXiv_csAR_bot/
- Is Exchangeability better than I.I.D to handle Data Distribution Shifts while Pooling Data for Da...
Ayush Roy, Samin Enam, Jun Xia, Won Hwa Kim, Vishnu Suresh Lokhande
arxiv.org/abs/2507.19575 mastoxiv.page/@arXiv_csCV_bot/
- TASER: Table Agents for Schema-guided Extraction and Recommendation
Nicole Cho, Kirsty Fielding, William Watson, Sumitra Ganesh, Manuela Veloso
arxiv.org/abs/2508.13404 mastoxiv.page/@arXiv_csAI_bot/
- Morphology-Aware Peptide Discovery via Masked Conditional Generative Modeling
Nuno Costa, Julija Zavadlav
arxiv.org/abs/2509.02060 mastoxiv.page/@arXiv_qbioBM_bo
- PCPO: Proportionate Credit Policy Optimization for Aligning Image Generation Models
Jeongjae Lee, Jong Chul Ye
arxiv.org/abs/2509.25774 mastoxiv.page/@arXiv_csCV_bot/
- Multi-hop Deep Joint Source-Channel Coding with Deep Hash Distillation for Semantically Aligned I...
Didrik Bergstr\"om, Deniz G\"und\"uz, Onur G\"unl\"u
arxiv.org/abs/2510.06868 mastoxiv.page/@arXiv_csIT_bot/
- MoMaGen: Generating Demonstrations under Soft and Hard Constraints for Multi-Step Bimanual Mobile...
Chengshu Li, et al.
arxiv.org/abs/2510.18316 mastoxiv.page/@arXiv_csRO_bot/
- A Spectral Framework for Graph Neural Operators: Convergence Guarantees and Tradeoffs
Roxanne Holden, Luana Ruiz
arxiv.org/abs/2510.20954 mastoxiv.page/@arXiv_statML_bo
- Breaking Agent Backbones: Evaluating the Security of Backbone LLMs in AI Agents
Bazinska, Mathys, Casucci, Rojas-Carulla, Davies, Souly, Pfister
arxiv.org/abs/2510.22620 mastoxiv.page/@arXiv_csCR_bot/
- Uncertainty Calibration of Multi-Label Bird Sound Classifiers
Raphael Schwinger, Ben McEwen, Vincent S. Kather, Ren\'e Heinrich, Lukas Rauch, Sven Tomforde
arxiv.org/abs/2511.08261 mastoxiv.page/@arXiv_csSD_bot/
- Two-dimensional RMSD projections for reaction path visualization and validation
Rohit Goswami (Institute IMX and Lab-COSMO, \'Ecole polytechnique f\'ed\'erale de Lausanne)
arxiv.org/abs/2512.07329 mastoxiv.page/@arXiv_physicsch
- Distribution-informed Online Conformal Prediction
Dongjian Hu, Junxi Wu, Shu-Tao Xia, Changliang Zou
arxiv.org/abs/2512.07770 mastoxiv.page/@arXiv_statML_bo
- Coupling Experts and Routers in Mixture-of-Experts via an Auxiliary Loss
Ang Lv, Jin Ma, Yiyuan Ma, Siyuan Qiao
arxiv.org/abs/2512.23447 mastoxiv.page/@arXiv_csCL_bot/
toXiv_bot_toot

@inthehands@hachyderm.io
2026-01-29 17:42:03

Meanwhile, Schumer’s much-touted list of demands is (oh, shocker) pathetic weak sauce: “a prohibition on [ICE] wearing masks, the imposition of a code of conduct and independent investigations of violations.”
…which, like…
(1) Sure, that would be nice — comically insufficient, but nice
(2) DHS already ignore the very clear laws that are on the books; why on earth do you think it would help to have more rules for them to ignore?
(3) ICE CBP right now are basically the KKK except with a budget the size of Russia’s military. Decimate that budget or GTFO.
theguardian.com/us-news/2026/j

@pavelasamsonov@mastodon.social
2026-02-26 15:43:13

#AI coding tools have shown that you can't iterate from bad software to good software.
Not that it is *physically* impossible, but that the context of the work prevents it. Instead of refining products with more feedback loops, management demands more new feature releases.
But no amount of "MVPs" add up to a mature product. No amount of bad code adds up to good code.
…

@arXiv_csCL_bot@mastoxiv.page
2026-03-31 11:13:03

Replaced article(s) found for cs.CL. arxiv.org/list/cs.CL/new
[4/5]:
- Retrieving Climate Change Disinformation by Narrative
Upravitelev, Solopova, Jakob, Sahitaj, M\"oller, Schmitt
arxiv.org/abs/2603.22015 mastoxiv.page/@arXiv_csCL_bot/
- PaperVoyager : Building Interactive Web with Visual Language Models
Dasen Dai, Biao Wu, Meng Fang, Wenhao Wang
arxiv.org/abs/2603.22999 mastoxiv.page/@arXiv_csCL_bot/
- Continual Robot Skill and Task Learning via Dialogue
Weiwei Gu, Suresh Kondepudi, Anmol Gupta, Lixiao Huang, Nakul Gopalan
arxiv.org/abs/2409.03166 mastoxiv.page/@arXiv_csRO_bot/
- Shifting Perspectives: Steering Vectors for Robust Bias Mitigation in LLMs
Zara Siddique, Irtaza Khalid, Liam D. Turner, Luis Espinosa-Anke
arxiv.org/abs/2503.05371 mastoxiv.page/@arXiv_csLG_bot/
- SkillFlow: Scalable and Efficient Agent Skill Retrieval System
Fangzhou Li, Pagkratios Tagkopoulos, Ilias Tagkopoulos
arxiv.org/abs/2504.06188 mastoxiv.page/@arXiv_csAI_bot/
- Large Language Models for Computer-Aided Design: A Survey
Licheng Zhang, Bach Le, Naveed Akhtar, Siew-Kei Lam, Tuan Ngo
arxiv.org/abs/2505.08137 mastoxiv.page/@arXiv_csLG_bot/
- Structured Agent Distillation for Large Language Model
Liu, Kong, Dong, Yang, Li, Tang, Yuan, Niu, Zhang, Zhao, Lin, Huang, Wang
arxiv.org/abs/2505.13820 mastoxiv.page/@arXiv_csLG_bot/
- VLM-3R: Vision-Language Models Augmented with Instruction-Aligned 3D Reconstruction
Fan, Zhang, Li, Zhang, Chen, Hu, Wang, Qu, Zhou, Wang, Yan, Xu, Theiss, Chen, Li, Tu, Wang, Ranjan
arxiv.org/abs/2505.20279 mastoxiv.page/@arXiv_csCV_bot/
- Learning to Diagnose Privately: DP-Powered LLMs for Radiology Report Classification
Bhattacharjee, Tian, Rubin, Lo, Merchant, Hanson, Gounley, Tandon
arxiv.org/abs/2506.04450 mastoxiv.page/@arXiv_csCR_bot/
- L-MARS: Legal Multi-Agent Workflow with Orchestrated Reasoning and Agentic Search
Ziqi Wang, Boqin Yuan
arxiv.org/abs/2509.00761 mastoxiv.page/@arXiv_csAI_bot/
- Your Models Have Thought Enough: Training Large Reasoning Models to Stop Overthinking
Han, Huang, Liao, Jiang, Lu, Zhao, Wang, Zhou, Jiang, Liang, Zhou, Sun, Yu, Xiao
arxiv.org/abs/2509.23392 mastoxiv.page/@arXiv_csAI_bot/
- Person-Centric Annotations of LAION-400M: Auditing Bias and Its Transfer to Models
Leander Girrbach, Stephan Alaniz, Genevieve Smith, Trevor Darrell, Zeynep Akata
arxiv.org/abs/2510.03721 mastoxiv.page/@arXiv_csCV_bot/
- Agentic Context Engineering: Evolving Contexts for Self-Improving Language Models
Zhang, Hu, Upasani, Ma, Hong, Kamanuru, Rainton, Wu, Ji, Li, Thakker, Zou, Olukotun
arxiv.org/abs/2510.04618 mastoxiv.page/@arXiv_csLG_bot/
- Mitigating Premature Exploitation in Particle-based Monte Carlo for Inference-Time Scaling
Giannone, Xu, Nayak, Awhad, Sudalairaj, Xu, Srivastava
arxiv.org/abs/2510.05825 mastoxiv.page/@arXiv_csLG_bot/
- Complete asymptotic type-token relationship for growing complex systems with inverse power-law co...
Pablo Rosillo-Rodes, Laurent H\'ebert-Dufresne, Peter Sheridan Dodds
arxiv.org/abs/2511.02069 mastoxiv.page/@arXiv_physicsso
- ViPRA: Video Prediction for Robot Actions
Sandeep Routray, Hengkai Pan, Unnat Jain, Shikhar Bahl, Deepak Pathak
arxiv.org/abs/2511.07732 mastoxiv.page/@arXiv_csRO_bot/
- AISAC: An Integrated multi-agent System for Transparent, Retrieval-Grounded Scientific Assistance
Chandrachur Bhattacharya, Sibendu Som
arxiv.org/abs/2511.14043
- VideoARM: Agentic Reasoning over Hierarchical Memory for Long-Form Video Understanding
Yufei Yin, Qianke Meng, Minghao Chen, Jiajun Ding, Zhenwei Shao, Zhou Yu
arxiv.org/abs/2512.12360 mastoxiv.page/@arXiv_csCV_bot/
- RadImageNet-VQA: A Large-Scale CT and MRI Dataset for Radiologic Visual Question Answering
L\'eo Butsanets, Charles Corbi\`ere, Julien Khlaut, Pierre Manceron, Corentin Dancette
arxiv.org/abs/2512.17396 mastoxiv.page/@arXiv_csCV_bot/
- Measuring all the noises of LLM Evals
Sida Wang
arxiv.org/abs/2512.21326 mastoxiv.page/@arXiv_csLG_bot/
toXiv_bot_toot