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Context Compression Is Not One Thing: Readable Symbolic Re-expression vs. Coherent Summary at Matched Budget
Sisong Bei, Mikhail L. Arbuzov, Ziwei Dong +2
We study context compression for multi-hop question answering with small language models. We propose Telegraph English, a readable symbolic format that rewrites retrieved passages…
The Architecture of Errors: From Universal Impossibility to Patch-Local LLM Reliability
Mikhail L. Arbuzov, Lee Mosbacker, Sisong Bei +3
Universal LLM reliability is not a finite-library problem: across all possible tasks, tools, schemas, knowledge sources, and evaluator expectations, new intervention-distinguishabl…
Telegraph English: Semantic Prompt Compression via Structured Symbolic Rewriting
Mikhail L. Arbuzov, Sisong Bei, Ziwei Dong +2
We introduce Telegraph English (TE), a prompt-compression protocol that rewrites natural language into a symbol-rich, formally-structured dialect. Where token-deletion methods such…
Beyond Exponential Decay: Rethinking Error Accumulation in Large Language Models
Mikhail L. Arbuzov, Sisong Bei, Ziwei Dong +2
The prevailing assumption of an exponential decay in large language model (LLM) reliability with sequence length, predicated on independent per-token error probabilities, posits an…