Tootfinder

🇺🇦 #NowPlaying on KEXP's #VarietyMix
Quadeca:
🎵 GODSTAINED
#Quadeca
https://quadecax8.bandcamp.com/track/godstained
https://open.spotify.com/track/2IbtNIdNlVelpPNaRYEZdJ

Is NSC al haar lijden verlost?
@nlpol #stemmingen #politiek

Scaling LLM Planning: NL2FLOW for Parametric Problem Generation and Rigorous Evaluation
Jungkoo Kang
https://arxiv.org/abs/2507.02253 https://

Scaling LLM Planning: NL2FLOW for Parametric Problem Generation and Rigorous Evaluation
Progress in enhancing large language model (LLM) planning and reasoning capabilities is significantly hampered by the bottleneck of scalable, reliable data generation and evaluation. To overcome this, I introduce NL2FLOW, a fully automated system for parametrically generating planning problems - expressed in natural language, a structured intermediate representation, and formal PDDL - and rigorously evaluating the quality of generated plans. I demonstrate NL2FLOW's capabilities by generating a …

Uiteraard valt t kwartje niet in Israel.
(Maar we gaan eerst maar zien wat er aan daadwerkelijke maatregelen genomen worden.)
Gejat bij de buren (bs, ‪@drjohamsterdam.bsky.social)
@nlpol
#RedLine #RodeLijn

The Dutch left just forced every other party to show their hand and their hand is "we don't actually mind what Israel is doing that much".
#nlpol

LLM-Based Repair of Static Nullability Errors
Nima Karimipour, Michael Pradel, Martin Kellogg, Manu Sridharan
https://arxiv.org/abs/2507.20674 https://arxi…

LLM-Based Repair of Static Nullability Errors
Modern Java projects increasingly adopt static analysis tools that prevent null-pointer exceptions by treating nullness as a type property. However, integrating such tools into large, existing codebases remains a significant challenge. While annotation inference can eliminate many errors automatically, a subset of residual errors -- typically a mix of real bugs and false positives -- often persist and can only be resolved via code changes. Manually addressing these errors is tedious and error-p…

NLI4VolVis: Natural Language Interaction for Volume Visualization via LLM Multi-Agents and Editable 3D Gaussian Splatting
Kuangshi Ai, Kaiyuan Tang, Chaoli Wang
https://arxiv.org/abs/2507.12621

NLI4VolVis: Natural Language Interaction for Volume Visualization via LLM Multi-Agents and Editable 3D Gaussian Splatting
Traditional volume visualization (VolVis) methods, like direct volume rendering, suffer from rigid transfer function designs and high computational costs. Although novel view synthesis approaches enhance rendering efficiency, they require additional learning effort for non-experts and lack support for semantic-level interaction. To bridge this gap, we propose NLI4VolVis, an interactive system that enables users to explore, query, and edit volumetric scenes using natural language. NLI4VolVis int…

🇺🇦 #NowPlaying on BBCRadio3's #InTune
Wolfgang Amadeus Mozart, Neil Black & Academy of St Martin in the Fields Chamber Ensemble:
🎵 Oboe Quartet in F major, K 370 (1st mvt)
#WolfgangAmadeusMozart #NeilBlack #AcademyofStMartinintheFieldsChamberEnsemble

🇺🇦 #NowPlaying on #KEXP's #90TEEN
Pelada:
🎵 No Hay
#Pelada
https://newlabel.bandcamp.com/album/new002-pelada-no-hay-ten-cuidado-ep
https://open.spotify.com/track/3e78dDMhWG4CAnrlL5G6EM
🎶 show playlist 👇
https://open.spotify.com/playlist/20Rz1l3z2ghKiLzcxe3HpQ
🎶 KEXP playlist 👇
https://open.spotify.com/playlist/6VNALrOa3gWbk794YuIrwg