Researchers propose a value-of-information router for block-sparse attention that dynamically doubles the kept key blocks when the top-k selection is uncertain, improving recall on LongBench-v2 from 0…
Researchers propose Jet-Long, a tuning-free zero-shot method for extending LLM context windows that dynamically adjusts a rescaling factor based on sequence length, preserving short-context fidelity w…
A developer observed that after multiple context compactions in LLM sessions, output quality degrades non-linearly, with a brief improvement after the second compaction before declining. They built a …
Researchers introduced Still, a per-layer Perceiver model that compacts KV cache in a single forward pass, enabling efficient long-context language model deployment. On Qwen and Gemma models, Still ou…
Chroma tested 18 frontier AI models including GPT-4.1, Claude Opus 4, and Gemini 2.5 Pro, finding that every model's performance degrades as context length grows, contradicting vendor claims of 1M-2M …
A new analysis warns that large language model context windows degrade significantly beyond 100k tokens, making advertised sizes of 200k to 2M tokens misleading for practical use. Studies like RULER a…
Researchers introduced RULER, a set of representation-level verification metrics for machine unlearning, after finding that current output-level tests can pass even when models retain forgotten data i…