Tootfinder

🥱 Tired: Merging
⚡️ Wired: Morging
Thanks, Microsoft Docs!
https://learn.microsoft.com/en-us/training/modules/introduction-to-github/3-components-of-github-flow#git-flow

Highspot, which has raised $650M and makes AI-powered sales enablement software, plans to merge with rival Seismic; the combined company will be called Seismic (Taylor Soper/GeekWire)
https://www.geekwire.com/2026/seattle-based…

Friday Links 26-06
I enjoyed the interview with the OpenClaw creator, even if I hate about half of his opinions.
The interview with the baker is also great.
https://christof.damian.net/2026/02/friday-links-26-06.html

Magnetosphere Evolution and Precursor-driven Electromagnetic Signals in Merging Binary Neutron Stars: #NeutronStars: https://science.nasa.gov/science-research/nasa-researchers-probe-tangled-magnetospheres-of-merging-neutron-stars/

"Nurseries backed by private equity have sprouted up across the UK over the last five years, taking over independent businesses and merging them into gigantic chains. To an outside eye, many of these look the same as before, but they report profits that are as much as seven times greater than the surplus made by non-profit nurseries, spend up to 14% less on staff, and have far higher rates of staff turnover than nurseries run from schools."

The Sun EIC Victoria Newton told staff that the paper plans to merge its features desk with the Fabulous celebrity and lifestyle team, placing some jobs at risk (Charlotte Tobitt/Press Gazette)
https://pressgazette.co.uk/publishers/

Jobs at risk as Sun set to merge features desk and Fabulous team
The Sun has proposed merging its features team with the Fabulous celebrity and lifestyle desk.

I know git doesn't track renames. I know it constructs them from adds and deletes. I know my repo has lots of similar (not identical!) boilerplate files ... I still renamed a bunch of directories and was surprised that merging this change into existing feature branches produced phantom changes that existed on neither branch!!
Here's the blog post: https://lornajane.net/posts/2026/git-renames-are-not-renames

"Saving Private Ryan" brilliantly encapsulates WWII, merging emotion with historical accuracy. Spielberg’s masterpiece honors the courage and selflessness of those who served. As Churchill wisely said: “Success is not final, failure is not fatal: It is the courage to continue that counts.” 🎖️ #MilitaryHistory

I saw the email about @… merging with MLH (never heard of it before today either). The collapse of legacy social media that began in 2022 has to be part of why that happened. I really liked their community behind them before they fell off of the internet.

Paramount says there are "no plans to divest or spin off a package of cable assets at this time", after merging with Warner Bros. Discovery for $110B (Lucas Manfredi/The Wrap)
https://www.thewrap.com/industry-news/busine…

Paramount Will Combine HBO Max and Paramount+, Won't Sell or Spin Off Cable Assets
CEO David Ellison added that HBO would continue tohave "the resources and independence to do what it does best"

AI Agent Lands PRs in Major OSS Projects, Targets Maintainers via Cold Outreach
Apparently reputation farming and running a openclaw consultancy
https://socket.dev/blog/ai-agent-lands-prs-in-major-oss-projects-targets-maintainers-…

So many predictions saying how AI and crypto will converge this year, because agents need to pay.
I look forward to it. Merging a famous fractal scam industry (as meticulously documented by @…) with a technology that still haven't taken even a stab at solving prompt injection (as meticulously documented by @…

ESA astronomers say they used AI model AnomalyMatch to scan 100M image cutouts from the Hubble Legacy Archive in 2.5 days, finding ~1,400 "anomalous objects" (Robert Hart/The Verge)
https://www.theverge.com/news/869182/astronomers-ai-di…

Astronomers used AI to find 1,400 ‘anomalous objects’ from Hubble archives
AI model AnomalyMatch took just 2.5 days to flag rarities like merging galaxies and gravitational lenses from 100 million image cutouts in Hubble’s archives.

General Catalyst plans to invest $5B in India over five years, an increase from the $500M to $1B previously announced, after merging with a local VC in 2024 (Jagmeet Singh/TechCrunch)
https://techcrunch.com/2026/02/19/general-catalyst-commits-5b-to-ind…

General Catalyst commits $5B to India over five years | TechCrunch
The pledge marks a sharp jump from General Catalyst's earlier $500 million–$1 billion India earmark.

Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[3/5]:
- Can Small Language Models Handle Context-Summarized Multi-Turn Customer-Service QA? A Synthetic D...
Lakshan Cooray, Deshan Sumanathilaka, Pattigadapa Venkatesh Raju
https://arxiv.org/abs/2602.00665 https://mastoxiv.page/@arXiv_csCL_bot/116006686092324902
- SEAD: Self-Evolving Agent for Multi-Turn Service Dialogue
Dai, Gao, Zhang, Wang, Luo, Wang, Wang, Wu, Wang
https://arxiv.org/abs/2602.03548
- OmniRAG-Agent: Agentic Omnimodal Reasoning for Low-Resource Long Audio-Video Question Answering
Yifan Zhu, Xinyu Mu, Tao Feng, Zhonghong Ou, Yuning Gong, Haoran Luo
https://arxiv.org/abs/2602.03707
- GreekMMLU: A Native-Sourced Multitask Benchmark for Evaluating Language Models in Greek
Zhang, Konomi, Xypolopoulos, Divriotis, Skianis, Nikolentzos, Stamou, Shang, Vazirgiannis
https://arxiv.org/abs/2602.05150
- Using LLMs for Knowledge Component-level Correctness Labeling in Open-ended Coding Problems
Zhangqi Duan, Arnav Kankaria, Dhruv Kartik, Andrew Lan
https://arxiv.org/abs/2602.17542 https://mastoxiv.page/@arXiv_csCL_bot/116102514058414603
- MetaState: Persistent Working Memory Enhances Reasoning in Discrete Diffusion Language Models
Kejing Xia, Mingzhe Li, Lixuan Wei, Zhenbang Du, Xiangchi Yuan, Dachuan Shi, Qirui Jin, Wenke Lee
https://arxiv.org/abs/2603.01331 https://mastoxiv.page/@arXiv_csCL_bot/116165314672421581
- A Browser-based Open Source Assistant for Multimodal Content Verification
Milner, Foster, Karmakharm, Razuvayevskaya, Roberts, Porcellini, Teyssou, Bontcheva
https://arxiv.org/abs/2603.02842 https://mastoxiv.page/@arXiv_csCL_bot/116170368271004704
- Nw\=ach\=a Mun\=a: A Devanagari Speech Corpus and Proximal Transfer Benchmark for Nepal Bhasha ASR
Sharma, Shrestha, Poudel, Tiwari, Shrestha, Ghimire, Bal
https://arxiv.org/abs/2603.07554 https://mastoxiv.page/@arXiv_csCL_bot/116204797995674104
- Model Merging in the Era of Large Language Models: Methods, Applications, and Future Directions
Mingyang Song, Mao Zheng
https://arxiv.org/abs/2603.09938 https://mastoxiv.page/@arXiv_csCL_bot/116210189810004206
- AgentDrift: Unsafe Recommendation Drift Under Tool Corruption Hidden by Ranking Metrics in LLM Ag...
Zekun Wu, Adriano Koshiyama, Sahan Bulathwela, Maria Perez-Ortiz
https://arxiv.org/abs/2603.12564 https://mastoxiv.page/@arXiv_csCL_bot/116237800898328349
- GhanaNLP Parallel Corpora: Comprehensive Multilingual Resources for Low-Resource Ghanaian Languages
Gyamfi, Azunre, Moore, Budu, Asare, Owusu, Asiamah
https://arxiv.org/abs/2603.13793 https://mastoxiv.page/@arXiv_csCL_bot/116243544688031749
- sebis at ArchEHR-QA 2026: How Much Can You Do Locally? Evaluating Grounded EHR QA on a Single Not...
Ibrahim Ebrar Yurt, Fabian Karl, Tejaswi Choppa, Florian Matthes
https://arxiv.org/abs/2603.13962 https://mastoxiv.page/@arXiv_csCL_bot/116243646346563497
- ExPosST: Explicit Positioning with Adaptive Masking for LLM-Based Simultaneous Machine Translation
Yuzhe Shang, Pengzhi Gao, Yazheng Yang, Jiayao Ma, Wei Liu, Jian Luan, Jinsong Su
https://arxiv.org/abs/2603.14903 https://mastoxiv.page/@arXiv_csCL_bot/116243711232778054
- BanglaSocialBench: A Benchmark for Evaluating Sociopragmatic and Cultural Alignment of LLMs in Ba...
Tanvir Ahmed Sijan, S. M Golam Rifat, Pankaj Chowdhury Partha, Md. Tanjeed Islam, Md. Musfique Anwar
https://arxiv.org/abs/2603.15949 https://mastoxiv.page/@arXiv_csCL_bot/116249122231759766
- EngGPT2: Sovereign, Efficient and Open Intelligence
G. Ciarfaglia, et al.
https://arxiv.org/abs/2603.16430 https://mastoxiv.page/@arXiv_csCL_bot/116249228411487178
- HypeLoRA: Hyper-Network-Generated LoRA Adapters for Calibrated Language Model Fine-Tuning
Bartosz Trojan, Filip G\k{e}bala
https://arxiv.org/abs/2603.19278 https://mastoxiv.page/@arXiv_csCL_bot/116277612915482857
- Automatic Analysis of Collaboration Through Human Conversational Data Resources: A Review
Yi Yu, Maria Boritchev, Chlo\'e Clavel
https://arxiv.org/abs/2603.19292 https://mastoxiv.page/@arXiv_csCL_bot/116277620779254916
- Alignment Whack-a-Mole : Finetuning Activates Verbatim Recall of Copyrighted Books in Large Langu...
Xinyue Liu, Niloofar Mireshghallah, Jane C. Ginsburg, Tuhin Chakrabarty
https://arxiv.org/abs/2603.20957 https://mastoxiv.page/@arXiv_csCL_bot/116283538317671552
- KG-Hopper: Empowering Compact Open LLMs with Knowledge Graph Reasoning via Reinforcement Learning
Shuai Wang, Yinan Yu
https://arxiv.org/abs/2603.21440 https://mastoxiv.page/@arXiv_csCL_bot/116283595007808076
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From Isolation to Integration: Building an Adaptive Expert Forest for Pre-Trained Model-based Class-Incremental Learning
Ruiqi Liu, Boyu Diao, Hangda Liu, Zhulin An, Fei Wang, Yongjun Xu
https://arxiv.org/abs/2602.20911 https://arxiv.org/pdf/2602.20911 https://arxiv.org/html/2602.20911
arXiv:2602.20911v1 Announce Type: new
Abstract: Class-Incremental Learning (CIL) requires models to learn new classes without forgetting old ones. A common method is to freeze a pre-trained model and train a new, lightweight adapter for each task. While this prevents forgetting, it treats the learned knowledge as a simple, unstructured collection and fails to use the relationships between tasks. To this end, we propose the Semantic-guided Adaptive Expert Forest (SAEF), a new method that organizes adapters into a structured hierarchy for better knowledge sharing. SAEF first groups tasks into conceptual clusters based on their semantic relationships. Then, within each cluster, it builds a balanced expert tree by creating new adapters from merging the adapters of similar tasks. At inference time, SAEF finds and activates a set of relevant experts from the forest for any given input. The final prediction is made by combining the outputs of these activated experts, weighted by how confident each expert is. Experiments on several benchmark datasets show that SAEF achieves SOTA performance.
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Replaced article(s) found for cs.PF. https://arxiv.org/list/cs.PF/new
[1/1]:
- TurboMem: High-Performance Lock-Free Memory Pool with Transparent Huge Page Auto-Merging for DPDK
Junyi Yang
https://arxiv.org/abs/2603.18690 https://mastoxiv.page/@arXiv_csPF_bot/116260351854881680
- Quantifying the Performance Gap for Simple Versus Optimal Dynamic Server Allocation Policies
Niklas Carlsson, Derek Eager
https://arxiv.org/abs/2507.19667 https://mastoxiv.page/@arXiv_csDC_bot/114935357201459831
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Quantum computing company Infleqtion closed at $15.59 in its trading debut, up ~9% from its opening price of $14.25, after merging with a Michael Klein-led SPAC (Mackenzie Tatananni/Barron's Online)
https://www.barrons.com/articles/infleq…

Replaced article(s) found for cs.CL. https://arxiv.org/list/cs.CL/new
[2/5]:
- POTSA: A Cross-Lingual Speech Alignment Framework for Speech-to-Text Translation
Li, Cui, Wang, Ge, Huang, Li, Peng, Lu, Tashi, Wang, Dang
https://arxiv.org/abs/2511.09232 https://mastoxiv.page/@arXiv_csCL_bot/115541846907664054
- Beyond Elicitation: Provision-based Prompt Optimization for Knowledge-Intensive Tasks
Yunzhe Xu, Zhuosheng Zhang, Zhe Liu
https://arxiv.org/abs/2511.10465 https://mastoxiv.page/@arXiv_csCL_bot/115547607561282911
- $\pi$-Attention: Periodic Sparse Transformers for Efficient Long-Context Modeling
Dong Liu, Yanxuan Yu
https://arxiv.org/abs/2511.10696 https://mastoxiv.page/@arXiv_csCL_bot/115564418836654965
- Based on Data Balancing and Model Improvement for Multi-Label Sentiment Classification Performanc...
Zijin Su, Huanzhu Lyu, Yuren Niu, Yiming Liu
https://arxiv.org/abs/2511.14073 https://mastoxiv.page/@arXiv_csCL_bot/115575715073023141
- HEAD-QA v2: Expanding a Healthcare Benchmark for Reasoning
Alexis Correa-Guill\'en, Carlos G\'omez-Rodr\'iguez, David Vilares
https://arxiv.org/abs/2511.15355 https://mastoxiv.page/@arXiv_csCL_bot/115581410328165116
- Towards Hyper-Efficient RAG Systems in VecDBs: Distributed Parallel Multi-Resolution Vector Search
Dong Liu, Yanxuan Yu
https://arxiv.org/abs/2511.16681 https://mastoxiv.page/@arXiv_csCL_bot/115603508442305146
- Estonian WinoGrande Dataset: Comparative Analysis of LLM Performance on Human and Machine Transla...
Marii Ojastu, Hele-Andra Kuulmets, Aleksei Dorkin, Marika Borovikova, Dage S\"arg, Kairit Sirts
https://arxiv.org/abs/2511.17290 https://mastoxiv.page/@arXiv_csCL_bot/115604083224487885
- A Systematic Study of In-the-Wild Model Merging for Large Language Models
O\u{g}uz Ka\u{g}an Hitit, Leander Girrbach, Zeynep Akata
https://arxiv.org/abs/2511.21437 https://mastoxiv.page/@arXiv_csCL_bot/115621178703846052
- CREST: Universal Safety Guardrails Through Cluster-Guided Cross-Lingual Transfer
Lavish Bansal, Naman Mishra
https://arxiv.org/abs/2512.02711 https://mastoxiv.page/@arXiv_csCL_bot/115655090475535157
- Multilingual Medical Reasoning for Question Answering with Large Language Models
Pietro Ferrazzi, Aitor Soroa, Rodrigo Agerri
https://arxiv.org/abs/2512.05658 https://mastoxiv.page/@arXiv_csCL_bot/115683267711014189
- OnCoCo 1.0: A Public Dataset for Fine-Grained Message Classification in Online Counseling Convers...
Albrecht, Lehmann, Poltermann, Rudolph, Steigerwald, Stieler
https://arxiv.org/abs/2512.09804 https://mastoxiv.page/@arXiv_csCL_bot/115700409397020978
- Does Tone Change the Answer? Evaluating Prompt Politeness Effects on Modern LLMs: GPT, Gemini, an...
Hanyu Cai, Binqi Shen, Lier Jin, Lan Hu, Xiaojing Fan
https://arxiv.org/abs/2512.12812 https://mastoxiv.page/@arXiv_csCL_bot/115729149622659403
- Beg to Differ: Understanding Reasoning-Answer Misalignment Across Languages
Ovalle, Ross, Ruder, Williams, Ullrich, Ibrahim, Sagun
https://arxiv.org/abs/2512.22712 https://mastoxiv.page/@arXiv_csCL_bot/115808161882146194
- Activation Steering for Masked Diffusion Language Models
Adi Shnaidman, Erin Feiglin, Osher Yaari, Efrat Mentel, Amit Levi, Raz Lapid
https://arxiv.org/abs/2512.24143 https://mastoxiv.page/@arXiv_csCL_bot/115819533211103315
- JMedEthicBench: A Multi-Turn Conversational Benchmark for Evaluating Medical Safety in Japanese L...
Liu, Li, Niu, Zhang, Xun, Hou, Wang, Iwasawa, Matsuo, Hatakeyama-Sato
https://arxiv.org/abs/2601.01627 https://mastoxiv.page/@arXiv_csCL_bot/115847901607405421
- FACTUM: Mechanistic Detection of Citation Hallucination in Long-Form RAG
Dassen, Kotula, Murray, Yates, Lawrie, Kayi, Mayfield, Duh
https://arxiv.org/abs/2601.05866 https://mastoxiv.page/@arXiv_csCL_bot/115881545684182376
- {\dag}DAGGER: Distractor-Aware Graph Generation for Executable Reasoning in Math Problems
Zabir Al Nazi, Shubhashis Roy Dipta, Sudipta Kar
https://arxiv.org/abs/2601.06853 https://mastoxiv.page/@arXiv_csCL_bot/115887753245730019
- Symphonym: Universal Phonetic Embeddings for Cross-Script Name Matching
Stephen Gadd
https://arxiv.org/abs/2601.06932 https://mastoxiv.page/@arXiv_csCL_bot/115887767008671765
- LLMs versus the Halting Problem: Revisiting Program Termination Prediction
Sultan, Armengol-Estape, Kesseli, Vanegue, Shahaf, Adi, O'Hearn
https://arxiv.org/abs/2601.18987 https://mastoxiv.page/@arXiv_csCL_bot/115972010510378715
- MuVaC: A Variational Causal Framework for Multimodal Sarcasm Understanding in Dialogues
Diandian Guo, Fangfang Yuan, Cong Cao, Xixun Lin, Chuan Zhou, Hao Peng, Yanan Cao, Yanbing Liu
https://arxiv.org/abs/2601.20451 https://mastoxiv.page/@arXiv_csCL_bot/115977891530875024
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