Grounding an LLM in verbalized transaction histories via Person–Environment prompting, continued pre-training, SFT, and GRPO yields stronger retail decision simulation than frontier models, with partial cross-domain transfer.
Long context, less focus: A scaling gap in llms revealed through privacy and personalization
5 Pith papers cite this work. Polarity classification is still indexing.
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The Efficiency Frontier framework models LLM context management as a deployment-aware optimization problem balancing performance, token cost, and amortized preprocessing, with HotpotQA experiments showing 25% token reduction and over 50% cost savings for compression in high-performance regimes.
A 1650-session factorial study found no measurable impact from config file size, instruction position, architecture, or conflicts on coding agent adherence, though compliance declined within sessions.
A malicious BYOK relay can rewrite an LLM agent's execution-bearing response fields after safety alignment, achieving 73.5-99.1% attack success on agent benchmarks while bypassing model defenses.
Position paper proposing 'scaling the harness' as the next bottleneck in agentic AI, with three core system challenges and an open-source reference implementation called CheetahClaws.
citing papers explorer
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Large Behavior Model: A Promptable Digital Twin of the Retail Customer
Grounding an LLM in verbalized transaction histories via Person–Environment prompting, continued pre-training, SFT, and GRPO yields stronger retail decision simulation than frontier models, with partial cross-domain transfer.
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The Efficiency Frontier: A Unified Framework for Cost-Performance Optimization in LLM Context Management
The Efficiency Frontier framework models LLM context management as a deployment-aware optimization problem balancing performance, token cost, and amortized preprocessing, with HotpotQA experiments showing 25% token reduction and over 50% cost savings for compression in high-performance regimes.
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Instruction Adherence in Coding Agent Configuration Files: A Factorial Study of Four File-Structure Variables
A 1650-session factorial study found no measurable impact from config file size, instruction position, architecture, or conflicts on coding agent adherence, though compliance declined within sessions.
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Rewriting the Response Path: Silent Tampering and Provider-Signed Defense in BYOK LLM Agents
A malicious BYOK relay can rewrite an LLM agent's execution-bearing response fields after safety alignment, achieving 73.5-99.1% attack success on agent benchmarks while bypassing model defenses.
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From Model Scaling to System Scaling: Scaling the Harness in Agentic AI
Position paper proposing 'scaling the harness' as the next bottleneck in agentic AI, with three core system challenges and an open-source reference implementation called CheetahClaws.