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Research2026-06-09 · source-backed
LLMs barely correct errors in their own reasoning traces but readily correct the identical claim when it's attributed to an external source. Relabeling a claim from the agent's own role to an external one raises the explicit-correction rate by 23 to 93 percentage points across model families. That's a massive, free lift, and it has direct implications for how you wire any review step. More on the practical move in skills.
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Hand a model a correct program and tell it to find and fix bugs. It will find bugs. arXiv 2609.10123, posted September 9, ran LLMs as blind iterative bug-fixers across multiple models and repair environments. The headline result is the ratio: the rate at which these loops dama...
arXiv 2609.03344, 294 points on HN, tracks transitions among uncoupled, coupled and persistently dependent users, and claims social transmission plus collective reinforcement can produce runaway dynamics past a critical adoption threshold. The same framework yields "cognitive...
Speculative Probing appends a trained soft prompt to the end of the target sequence, turning the speculative-decoding module recent LLMs already run into a sequence classifier. Because the KV cache is already resident in a speculative-decoding pipeline, classification adds neg...
arXiv 2608.23541 tested 11 verifier-scored optimization tasks under matched compute. Different model families do find structurally different solutions, and then a single round of reading each other's complete outputs erases exactly the diversity that justified using multiple m...
In layer-interleaved hybrid linear attention models, massive activations spike immediately before full-attention layers and can persist through intervening linear-attention layers as inter-spike plateaus. As full attention gets denser, the spikes connect into the stable morpho...
LivePlan watches a programming agent's trajectory with rule-based detectors that need zero model calls, waking an advisor LLM only on drift, repeated failed actions, or an imminent no-patch exit. On SWE-agent across five LLMs it raised resolution rates up to 15.2% (9.9% averag...
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