“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.”

“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.”

“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).”

“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.”

“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.”

“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.”

“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).”

“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.”

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

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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.”

“LLM lightweighting technology has evolved from the traditional 16bit to 8bit, 4bit, but now there is even more challenge to the 1bit area and technology to suppress memory consumption other than weight is attracting attention.”

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“The paper focuses on query-aware mixed-precision KV cache quantization.”

“The paper focuses on disaggregating LLM serving.”

“ProCache utilizes constraint-aware feature caching to accelerate Diffusion Transformers.”

“The paper focuses on accelerating Transformer inference using a layer-wise caching strategy.”

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“The research focuses on cache pollution control.”

“The paper focuses on computing only 2% vision tokens and reusing 98% for Vision-Language Inference.”

“The paper focuses on advancing cache-based few-shot classification.”

“The article likely details the technical implementation and performance evaluation of V-Rex.”

“The paper focuses on KV cache compression in the context of reasoning.”

“The paper likely discusses a cache-guided autoregressive diffusion model.”

“The article likely details the architecture, implementation, and performance evaluation of CXL-SpecKV, potentially comparing it to other KV-cache designs or serving frameworks.”

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“The paper focuses on Dynamic Cache Orchestration for LLM Accelerators through Predictive Management.”

“The article's context comes from ArXiv.”

“The article's focus is on optimizing KV cache for LLMs.”

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“The research focuses on decoding-time KV cache eviction with global attention.”

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“SWAN introduces a decompression-free KV-cache compression technique.”

“The research is published on ArXiv.”

“Kvcached is likely a system designed for serving LLMs.”

“LMCache increases LLM throughput by a factor of 3.”