# KAIST Published articles for KAIST. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Shifting Focus by Reliability: Geometric Fusion Modulation for Robust RGB-T Detection DevFeed: [Shifting Focus by Reliability: Geometric Fusion Modulation for Robust RGB-T Detection]() Original publisher: [Read original article]() Author: Liuyin Shi, Chengqi Li, Wenbo He Published: 2026-11-02T05:00:00Z Content type: article Language: en Sources: [arXiv: Machine Learning]() Topics: [Machine learning]() Tags: [cs-cv](), [cs-lg](), [datasets](), [detection](), [flir](), [kaist](), [latency](), [object](), [peft](), [prompt](), [quality](), [restoration](), [rgb](), [robust](), [signal](), [simulations](), [thermal](), [type]() ### AI overview PG-FM adapts RGB-thermal detectors to the estimated corruption type and severity in each modality, addressing the limits of input-independent parameter-efficient tuning without restoring the inputs. The approach is motivated by controlled corruption sweeps showing that corruption types diverge more as severity increases. In controlled simulations, it reportedly preserves clean-set performance and raises mAP50 by up to 20.8 points on FLIR and 19.9 points on KAIST; it also transfers without retraining to unmodified, naturally acquired external RGB-T datasets. The excerpt does not provide further implementation details or quantify results on those external datasets. ### Source excerpt arXiv:2610.41204v1 Announce Type: cross Abstract: RGB-thermal (RGB-T) object detectors combine visible and thermal imagery for robust detection, but signal corruption in either stream can substantially degrade accuracy. Restoration-based methods incur significant latency and do not consistently improve downstream accuracy, raising a more direct question: rather than restoring corrupted inputs, can we efficiently adapt the detector to their varying signal quality? Conventional PEFT offers an efficient route, but its input-independent corrections cannot track diverse test-time corruptions. Our controlled corruption sweeps show that corruption types have similar effects near clean conditions but diverge increasingly with severity, motivating corruption-aware, per-input adaptation. We therefore propose PG-FM (Prompt-Guided Feature Modulation), which adapts RGB-T object detectors to the estimated corruption type and severity of each modality. Under controlled RGB-T corruption simulations, PG-FM preserves clean-set performance, improves mAP50 by up to 20.8 points on FLIR and 19.9 points on KAIST, and transfers without retraining to unmodified, naturally acquired external RGB-T datasets. ## Chip Industry Week in Review: Fab expansion, AI hardware, and quantum advances DevFeed: [Chip Industry Week in Review: Fab expansion, AI hardware, and quantum advances]() Original publisher: [Read original article]() Author: The SE Staff Published: 2026-10-16T07:01:05Z Content type: news Language: en Sources: [Semiconductor Engineering]() Topics: [Chip design](), [High-Performance Computing](), [AI Infrastructure](), [Post-quantum cryptography](), [tsmc](), [Detection engineering]() Tags: [applied-materials](), [ase](), [asml](), [ayar-labs](), [business](), [business-news](), [chip](), [chipagents](), [cisco](), [compute](), [computing-news](), [cxmt](), [d-wave](), [faraday-technology](), [formfactor](), [fujifilm](), [global-unichip-corp](), [globalfoundries](), [ibm](), [ibm-research](), [ic-link-by-imec](), [idc](), [infineon](), [intel](), [kaist](), [keysight](), [langdao-silex](), [lattice](), [marvell](), [microchip](), [microsoft](), [mueon](), [news](), [nikon](), [nvidia](), [quantum](), [semiconductor](), [startups](), [week-in-review]() ### AI overview This semiconductor industry roundup covers fab expansion and investment, advances in memory and EUV, chip design tools and AI infrastructure, security developments, and quantum computing. It reports that AI demand is driving equipment spending and startup funding, while China-based companies are advancing memory and lithography prototypes. The article also describes new chip design automation research and security initiatives, alongside continuing constraints in manufacturing capacity and supply chains. ### Source excerpt Fab expansion accelerates; China advances memory and EUV; Teradyne's test deal; SEMICON West and OCP highlights; 3D SiP; TSMC and ASML signals; 300mm fab spending; optical and 3D-compute startups raise fresh funding; quantum HW advances. The post Chip Industry Week In Review appeared first on Semiconductor Engineering. ## Chip Industry Week In Review DevFeed: [Chip Industry Week In Review]() Original publisher: [Read original article]() Author: The SE Staff Published: 2026-10-09T07:01:17Z Content type: news Language: en Sources: [Semiconductor Engineering]() Topics: [tsmc](), [Chip design](), [clean energy data centers](), [AWS Trainium](), [finops](), [ai code review]() Tags: [ai-chips](), [amd](), [applied-materials](), [arm](), [arteris](), [asml](), [atomic-machines](), [brookings](), [business](), [business-news](), [c2i-semiconductors](), [cadence](), [canon](), [carl-zeiss](), [chip](), [cirrus-logic](), [computing-news](), [cornell-university](), [cset](), [darpa](), [data](), [data-center](), [draper](), [elephantech](), [fermilab](), [globalfoundries](), [honeywell-aerospace](), [huawei](), [ibm](), [industry](), [infineon](), [infleqtion](), [intel](), [intel-foundry](), [inventvm](), [ionq](), [kaist](), [news](), [semiconductor]() ### AI overview This semiconductor industry roundup covers manufacturing agreements, chip design and lithography advances, AI data center investment, export controls, security issues, and quantum computing. It also reports on new engineering tools, including agentic AI features for RF design and automated CI/CD testing workflows. ### Source excerpt $2B foundry pact; hyper-NA EUV; TSMC, Samsung financials; Canon readies nanoimprint; AI chips under scrutiny; $10T data center buildout; $1.5B SiC boost; chip smuggling; 800V power gains traction; quantum HW scales up; wireless EV road charging; sub-nm gate dielectrics; mobile fab. The post Chip Industry Week In Review appeared first on Semiconductor Engineering. ## IonQ | IonQ Achieves Quantum Breakthrough for Next-Generation Electric Batteries DevFeed: [IonQ | IonQ Achieves Quantum Breakthrough for Next-Generation Electric Batteries]() Original publisher: [Read original article]() Author: IonQ Staff Published: 2026-01-15T23:19:20Z Content type: article Language: en Sources: [IonQ]() Topics: [Quantum Computing](), [Ising]() Tags: [algorithm](), [batteries](), [car](), [chemistry](), [energy](), [hardware](), [hyundai](), [kaist](), [quantum](), [quantum-computing]() ### AI overview IonQ describes a quantum algorithm developed with Hyundai and research partners to simulate molecular reactions in lithium-ion batteries. The company says the algorithm uses trapped-ion quantum hardware and hybrid quantum-classical computing, and could eventually help battery engineers explore more efficient and higher-performing batteries. The research also identifies possible applications in drug development and climate modeling. ### Source excerpt Learn about developing a quantum computing algorithm to build a better electric car battery