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Related Articles from SNS
HiTokSR: A Coarse-to-Fine Tokenizer with Hierarchical Codebooks for High-Fidelity Real-World Image Super-Resolution
arXiv:2606.01157v1 Announce Type: new Abstract: Vector-quantized (VQ) generative models have shown promising results in real-world image super-resolution (Real-ISR). However, existing methods typically rely on a monolithic latent space that entangles low-frequency structures with high-frequency textures. This entanglement forces a single codebook to capture a combinatorially complex set of structure-texture pairings, which constrains representational capacity and limits codebook utilization.
Predictable Compression Failures: Order Sensitivity and Information Budgeting for Evidence-Grounded Binary Adjudication
arXiv:2509.11208v3 Announce Type: replace-cross Abstract: Transformers used for evidence-grounded binary adjudication (e.g., support/refute, yes/no, or verifier-backed pass/fail decisions) can be sensitive to the order in which exchangeable evidence is presented, producing dispersion across permutations and unreliable attempted answers under a verifier-relative Bernoulli predicate. We treat evidence order as a nuisance variable and formalize an expectation-realization gap: next-token...
CacheRAG: A Semantic Caching System for Retrieval-Augmented Generation in Knowledge Graph Question Answering
arXiv:2604.26176v3 Announce Type: replace Abstract: The integration of Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) has significantly advanced Knowledge Graph Question Answering (KGQA). However, existing LLM-driven KGQA systems act as stateless planners, generating retrieval plans in isolation without exploiting historical query patterns: analogous to a database system that optimizes every query from scratch without a plan cache. This fundamental design flaw leads...
Full Reverse Engineering of the TI-84 Plus Operating System
TI-84 Plus OS — Reverse-engineering notes: system overview Target: ti84plus.rom (1 MiB flash dump). OS self-identifies as 2.55MP. CPU: Zilog Z80 (16-bit address bus, 64 KiB logical space) with hardware flash/RAM paging.
From Agni 5 to Akash & hypersonics: Decoding India's homegrown arsenal & defence shield
The ongoing conflicts in Ukraine, on the borders of Israel and in the Persian Gulf have underscored the importance of indigenous defence technologies and a domestic industry to back innovation. India has been steadily working to become self-reliant in defence manufacturing. The country is now on a razor’s edge—designing, developing, and deploying homegrown defence technologies.
CacheRAG: A Semantic Caching System for Retrieval-Augmented Generation in Knowledge Graph Question Answering
arXiv:2604.26176v4 Announce Type: replace Abstract: The integration of Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) has significantly advanced Knowledge Graph Question Answering (KGQA). However, existing LLM-driven KGQA systems act as stateless planners, generating retrieval plans in isolation without exploiting historical query patterns: analogous to a database system that optimizes every query from scratch without a plan cache. This fundamental design flaw leads...
Make in India boost: Army tests Divyastra Mk-1 built for intel, surveillance; how it works?
In a major boost to India's indigenous defence technology ecosystem, Hoverit has successfully conducted an operational demonstration of its tactical loitering munition platform, Divyastra Mk-1, in Jodhpur in the presence of senior Indian Army leadership. As part of the demonstration, the Divyastra Mk-1 UAV was successfully launched multiple times from a vehicle-mounted mobile launcher configuration, showcasing the platform's rapid deployment capability, battlefield mobility, and tactical...
CacheRAG: A Semantic Caching System for Retrieval-Augmented Generation in Knowledge Graph Question Answering
Announce Type: replace Abstract: The integration of Large Language Models (LLMs) with Retrieval-Augmented Generation (RAG) has significantly advanced Knowledge Graph Question Answering (KGQA). However, existing LLM-driven KGQA systems act as stateless planners, generating retrieval plans in isolation without exploiting historical query patterns: analogous to a database system that optimizes every query from scratch without a plan cache. This fundamental design flaw leads to schema...