CodeMind evaluates ten LLMs on four benchmarks using three new code reasoning tasks, finding performance varies by model size and drops with complexity while showing no correlation with bug repair ability.
Reflex- ion: Language agents with verbal reinforcement learning
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
verdicts
UNVERDICTED 2representative citing papers
STARC remaps sparse KV caches by semantic clustering for PIM hardware, delivering 19-31% lower attention latency and 19-27% lower energy versus token-wise sparsity, with larger gains under tight KV budgets.
citing papers explorer
-
CodeMind: Evaluating Large Language Models for Code Reasoning
CodeMind evaluates ten LLMs on four benchmarks using three new code reasoning tasks, finding performance varies by model size and drops with complexity while showing no correlation with bug repair ability.
-
Sparse Attention Remapping with Clustering for Efficient LLM Decoding on PIM
STARC remaps sparse KV caches by semantic clustering for PIM hardware, delivering 19-31% lower attention latency and 19-27% lower energy versus token-wise sparsity, with larger gains under tight KV budgets.