CHESS: Context-aware Hierarchical Efficient Semantic Selection for Long-Context LLM Inference

CHESS: Context-aware Hierarchical Efficient Semantic Selection for Long-Context LLM Inference | Signal Canvas | ScienceToStartup

Page Freshness

Signal Canvas proof surface

Canonical route: /signal-canvas/chess-context-aware-hierarchical-efficient-semantic-selection-for-long-context-llm-inference

stale

Proof freshness: stale
Proof status: unverified
Display score: 8/10
Last proof check: 2026-03-19
Score updated: 2026-04-02
Score fresh until: 2026-05-02
References: 0
Source count: 0
Coverage: 33%

This page is showing the last landed evidence receipt and score bundle because the latest proof data is outside the freshness window.

Agent Handoff

Canonical ID chess-context-aware-hierarchical-efficient-semantic-selection-for-long-context-llm-inference | Route /signal-canvas/chess-context-aware-hierarchical-efficient-semantic-selection-for-long-context-llm-inference

REST example

curl https://sciencetostartup.com/api/v1/agent-handoff/signal-canvas/chess-context-aware-hierarchical-efficient-semantic-selection-for-long-context-llm-inference

MCP example

{
  "tool": "search_signal_canvas",
  "arguments": {
    "mode": "paper",
    "paper_ref": "chess-context-aware-hierarchical-efficient-semantic-selection-for-long-context-llm-inference",
    "query_text": "Summarize CHESS: Context-aware Hierarchical Efficient Semantic Selection for Long-Context LLM Inference"
  }
}

source_context

{
  "surface": "signal_canvas",
  "mode": "paper",
  "query": "CHESS: Context-aware Hierarchical Efficient Semantic Selection for Long-Context LLM Inference",
  "normalized_query": "2602.20732",
  "route": "/signal-canvas/chess-context-aware-hierarchical-efficient-semantic-selection-for-long-context-llm-inference",
  "paper_ref": "chess-context-aware-hierarchical-efficient-semantic-selection-for-long-context-llm-inference",
  "topic_slug": null,
  "benchmark_ref": null,
  "dataset_ref": null
}

Evidence Receipt

Route status: building

Claims: 8

References: Pending verification

Proof: Verification pending

Freshness state: computing

Source paper: CHESS: Context-aware Hierarchical Efficient Semantic Selection for Long-Context LLM Inference

PDF: https://arxiv.org/pdf/2602.20732v1

Source count: Pending verification

Coverage: 33%

Last proof check: 2026-03-19T21:31:49.672Z

Signal Canvas receipt window

Watch and verify: CHESS: Context-aware Hierarchical Efficient Semantic Selection for Long-Context LLM Inference

/buildability/chess-context-aware-hierarchical-efficient-semantic-selection-for-long-context-llm-inference

Watchwatch

Subject: CHESS: Context-aware Hierarchical Efficient Semantic Selection for Long-Context LLM Inference

Verdict

Watch

Verdict is Watch because viability or proof quality is intermediate and should be re-evaluated before execution.

Preparing verified analysis

GitHub Code Pulse

No public code linked for this paper yet.

Claim map

Strong 8Mixed 0Weak 0

Evidencepartial
delivers low-latency stable inference with up to 4.56x higher throughput
Implicationpartial
This is a direct quantitative result stated in the abstract and supported by the analysis.
Verificationpartial
partial
Evidencepartial
surpasses Full-KV quality using only 1% of the KV cache
Implicationpartial
This is a direct quantitative result stated in the abstract and supported by the analysis.
Verificationpartial
partial
Evidencepartial
we propose CHESS, an algorithm-system co-design KV-cache management system
Implicationpartial
This is a core description of the proposed system, explicitly stated in the abstract.
Verificationpartial
partial
Evidencepartial
CHESS introduces a context-aware, hierarchical selection policy that dynamically reconstructs a coherent context for the current decoding.
Implicationpartial
This describes the algorithmic approach of CHESS, as stated in the abstract and analysis.
Verificationpartial
partial
Evidencepartial
coarse granularity selection eliminates expensive data movement, fully realizing practical acceleration from theoretical sparsity.
Implicationpartial
This explains the system-level advantage of CHESS, as detailed in the abstract.
Verificationpartial
partial
Evidencepartial
CHESS could replace current LLM deployment strategies that are hampered by memory bandwidth limitations
Implicationpartial
This is an interpretation of the impact of CHESS, derived from the 'disruption' and 'why_it_matters' sections.
Verificationpartial
partial
Evidencepartial
The implementation may require adaptation to fit into diverse infrastructure environments
Implicationpartial
This is a potential limitation mentioned in the 'caveats' section of the analysis.
Verificationpartial
partial
Evidencepartial
there may be undiscovered edge cases where context-aware reconstruction might not perform optimally in real-world scenarios.
Implicationpartial
This is a potential limitation mentioned in the 'caveats' section of the analysis.
Verificationpartial
partial

Author intelligence and commercialization panels stay hidden until the proof receipt is verified, cites at least 3 references, includes at least 2 sources, and clears 50% coverage. The paper narrative and citation surfaces remain public while verification is pending.

CHESS: Context-aware Hierarchical Efficient Semantic Selection for Long-Context LLM Inference

Use Signal Canvas as the narrative proof surface

Use this Signal Canvas via API or MCP

Signal Canvas proof surface