“Suppliers of key components are temporarily halting production.”

“Announcement of a book club focusing on the book 『AI and Law: A Practical Encyclopedia』 by Taichi Kakinuma and Kenji Sugiura.”

“NVIDIA AI Open-Sourced KVzap: A SOTA KV Cache Pruning Method that Delivers near-Lossless 2x-4x Compression.”

“NVIDIA AI Open-Sourced KVzap: A SOTA KV Cache Pruning Method that Delivers near-Lossless 2x-4x Compression.”

“As context lengths move into tens and hundreds of thousands of tokens, the key value cache in transformer decoders becomes a primary deployment bottleneck.”

“Context Caching can slash input costs by up to 90%!”

“These findings suggest that the locus of AI intervention, rather than the amount of assistance, is critical in fostering writing self-efficacy while preserving learner agency.”

“By guiding LLMs with case-augmented reasoning instead of extensive code-like safety rules, we avoid rigid adherence to narrowly enumerated rules and enable broader adaptability.”

“Is Fitbit Premium, and its Gemini smarts, enough to justify its price?”

“The company used an AI-native platform to help companies fight threats.”

“The key is (1) 1B-class GGUF, (2) quantization (Q4 focused), (3) not increasing the KV cache too much, and configuring llama.cpp (=llama-server) tightly.”

“詳解します。”

“Max Tegmark wants to halt development of artificial superintelligence—and has Steve Bannon, Meghan Markle and will.i.am as supporters”

“A tool for spotting pancreatic cancer in routine CT scans has had promising results, one example of how China is racing to apply A.I. to medicine's tough problems.”

“Prompt caching is an optimization […]”

“due to being a hybrid transformer+mamba model, it stays fast as context fills”

“Gemini 3 Pro performed the best. It set up the fallback and cache effectively, with repeated generations returning in milliseconds from the cache. The run cost $0.45, took 7 minutes and 14 seconds, and used about 746K input (including cache reads) + ~11K output.”

“Vulcan synthesizes instance-optimal heuristics -- specialized for the exact workloads and hardware where they will be deployed -- using code-generating large language models (LLMs).”

“ProDM significantly improves CAC scoring accuracy, spatial lesion fidelity, and risk stratification performance compared with several baselines.”

“AODDiff inherently enables uncertainty quantification via multiple sampling, offering critical confidence metrics for downstream applications.”

“MEIC-DT achieves highly competitive coreference performance under stringent memory constraints.”

“PackKV achieves, on average, 153.2% higher memory reduction rate for the K cache and 179.6% for the V cache, while maintaining accuracy.”

“CorGi and CorGi+ achieve up to 2.0x speedup on average, while preserving high generation quality.”

“We’re in the midst of a global mental-­health crisis.”

“A goodness-of-fit test for the Zeta distribution with unknown parameter.”

“The model achieves an IoU of 0.9130 validating the success and efficacy of the "temporal-first" strategy.”

“CPePC bases its caching decisions by predicting a parameter whose value is estimated using current cache occupancy and the popularity of the content into account.”

“Outputs at any time t depend only on a fixed-length context window preceding t.”

“The paper's core contribution is "DivQAT, a novel algorithm to train quantized CNNs based on Quantization Aware Training (QAT) aiming to enhance their robustness against extraction attacks."”

“The study demonstrates the efficacy of periodic DLPNO-MP2 for probing increasingly sophisticated adsorption systems at the thermodynamic limit.”

“Trellis replaces the standard KV cache with a fixed-size memory and train a two-pass recurrent compression mechanism to store new keys and values into memory.”

“The models struggled to correctly classify human-written work (with error rates up to 32%).”

“LRH reduces Max/Avg load from 1.2785 to 1.0947 and achieves 60.05 Mkeys/s, about 6.8x faster than multi-probe consistent hashing with 8 probes (8.80 Mkeys/s) while approaching its balance (Max/Avg 1.0697).”

“The BR$k$NN-Light algorithm uses rapid verification and pruning strategies based on geometric constraints, along with an optimized range search technique, to speed up the process of identifying the R$k$NNs for each query.”

“What has your experience been with using q8 KV cache and a vision model? Would you say it’s good enough or does it ruin outputs?”

“Prompt Choreography significantly reduces per-message latency (2.0--6.2$ imes$ faster time-to-first-token) and achieves substantial end-to-end speedups ($>$2.2$ imes$) in some workflows dominated by redundant computation.”

“The paper introduces ByteLoom, a Diffusion Transformer (DiT)-based framework that generates realistic HOI videos with geometrically consistent object illustration, using simplified human conditioning and 3D object inputs.”

“ModelRunner receives the inference plan (SchedulerOutput) determined by the Scheduler and converts it into the execution of physical GPU kernels.”

“WeDLM preserves the quality of strong AR backbones while delivering substantial speedups, approaching 3x on challenging reasoning benchmarks and up to 10x in low-entropy generation regimes; critically, our comparisons are against AR baselines served by vLLM under matched deployment settings, demonstrating that diffusion-style decoding can outperform an optimized AR engine in practice.”

“The donors wish to remain anonymous.”

“The caching strategy is model-agnostic and can be applied to other off-the-shelf multi-view networks without retraining.”

“The results reveal that, in addition to the magnetic Bond number, the ratio of the drop-to-VH magnetic permeabilities plays a key role in the terminal shape parameters, like the retinal coverage.”

“KVCacheManager manages how to efficiently allocate the limited area of GPU VRAM.”

“Running out of iPhone space? Don't panic-buy a new phone or more iCloud+.”

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“We demonstrate that dynamic routing performs better than static averaging of schemes and achieves performance competitive with the MHA baseline while offering potential for conditional compute efficiency.”

“TimeBill proposes a fine-grained response length predictor (RLP) and an execution time estimator (ETE) to accurately predict the end-to-end execution time of LLMs.”

“The paper finds that idle conditions generally have the best distinguishability, while jitter and loaded conditions erode distinguishability. Cache-index and branch-style leakage tends to give the highest risk signals.”

“vLLM V1 introduces the KV Connector architecture to solve this problem.”

“The LAWPS framework reconstructs microbubble radius-time dynamics directly from passively recorded acoustic emissions.”