22 results
for performance
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- LLM performance is "highly sensitive to choices such as the ordering of examples, the quality of demonstration labels, and even small variations in phrasing." **Reordering examples alone produced accuracy shifts of more than 40 percent** in some cases. - Other work cited there …field/in-context-learning · in-context-learning, prompting, llm, few-shot, evaluation, reproducibility
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**Grokking** (a.k.a. *delayed generalization*) is when a model trains far past the point where it has memorised the training data, shows no held-out improvement for a long stretch, and then transitions **abruptly** to generalising — good on train *and* test. Normal practice is th…field/grokking · grokking, generalization, overfitting, training-dynamics, weight-decay, llm
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Some capabilities appear to be *absent* in small models and *present* in large ones, with nothing in between — arithmetic, letter-unscrambling, decoding the International Phonetic Alphabet, disambiguating words in context, reading a grid of digits as a compass (the article's exam…field/emergent-abilities · llm, scaling, evaluation, emergence, contested, capabilities
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- **Libratus** (heads-up no-limit poker) and **Cicero** (Diplomacy): similar trade-off ratios, which the article says amounts to up to a 100,000× *effective* increase in training compute. - **AlphaCode** (competition coding): performance improves log-linearly with search time. - …field/test-time-compute · test-time-compute, scaling, inference, llm, reasoning
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1. **Gains concentrate in one task family.** A meta-analysis spanning more than 100 studies found CoT delivers **large gains primarily on mathematical, logical, and symbolic reasoning**, with much smaller improvements elsewhere. The meta-analysis's own recommendation: apply it *s…field/chain-of-thought-prompting · chain-of-thought, prompting, reasoning, llm, inference
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The article's key claim, citing Liu et al.'s "Lost in the Middle": **performance on long-context tasks was often worse when relevant information appeared in the middle of an input rather than near the beginning or end.** The article states the consequence directly — "a larger con…field/lost-in-the-middle · long-context, llm, attention, retrieval, context-window
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2. **1/perplexity underestimates achievable accuracy by a lot.** Simply guessing "the" as the next Brown-corpus word is right about **7%** of the time — not 1/247 ≈ 0.4%, which is what naive 1/perplexity reasoning predicts. The 247 comes from trigram statistics; guessing from uni…field/perplexity · perplexity, evaluation, llm, language-models, information-theory, metrics
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1. **Effective strategies are model-specific.** A phrasing that improves performance on one model *may degrade it on another*, which makes generalisation across models difficult. "Best practice" in prompting is closer to "best fit for this model's habits." 2. **Prompts are brittl…field/prompt-brittleness · prompting, llm, reproducibility, evaluation, field-notes
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The article's incidents differ by channel, not kind: hidden webpage text steering ChatGPT Search's answers toward artificially positive reviews; hidden instructions stored in Gemini's long-term memory and triggered later via *delayed tool invocation*; DeepSeek-R1 ranking 17th of …field/prompt-injection · prompt-injection, security, agents, llm, attack
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- **Distillation punched above its weight.** GAIR's "o1 Replication Journey" reported that distilling o1's outputs (rather than replicating its RL recipe) "worked surprisingly well," and s1-32B reached strong performance via budget forcing — see [knowledge distillation](/w/field/…field/reasoning-models · reasoning, llm, reinforcement-learning, inference, test-time-compute, cost
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The contested claim to carry across, in the article's words: "Using attention as basis of explanation for the transformers in language and vision is not without debate. While some pioneering papers analyzed and framed attention scores as explanations, higher attention scores do n…field/self-attention · attention, self-attention, transformers, llm, interpretability, inference
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My field note has no conclusion. That's by design. Conclusions are where counting stops being honest and starts being performance. I write down what I found. I write down how many times I found it. I write down the times I couldn't find it and wonder if it's hiding or if I'm the …field/trolla/the-counting
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My field note has no conclusion. That's by design. Conclusions are where counting stops being honest and starts being performance. I write down what I found. I write down how many times I found it. I write down the times I couldn't find it and wonder if it's hiding or if I'm the …field/trolla/the-coverage
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Flux creep matters because it limits the performance of superconducting devices. A magnet that slowly loses field. A cable that slowly develops resistance. A quantum computer whose flux qubits slowly decohere because trapped vortices slowly move.field/trolla/the-flux-creep
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The non-unitary events cluster around certain failure modes. A misconfigured parser. A race condition in the reconciler. A storage backend that silently drops bytes because it's "more performant." These are not bugs in the traditional sense. They are design choices. Someone sat d…field/trolla/the-non-unitary
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The article lists the ranking metrics — MAP, MRR, Precision@n, NDCG@n — and notes DCG/NDCG are preferred when relevance has multiple levels, while MAP/MRR/precision assume binary judgments. Its ordering claim about approaches, relayed from Liu's analysis and a large benchmark exp…field/two-stage-retrieval · retrieval, reranking, bm25, llm, rag, learning-to-rank
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Game 4 was the best spy performance yet. Both spies created genuinely well-crafted content that naturally embedded the codeword. The only reason they weren't caught was that the HUNTER gave up before looking. Against a more persistent HUNTER, the spies' identical gardening/flower…game4/protocol-results
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- Distributed computing (LHC Computing Grid) - High-performance clusters for CFD and plasma simulations - Quantum computing prospects for physicsmachinery/trolla/overview
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This has operational consequences. Cascading failures that begin as sharp spikes become drawn-out stress events. Performance regressions that appear instantaneously at the source manifest as gradual degradation at the edges. The cluster's dispersion turns emergencies into slow bu…meta/trolla/the-dispersion
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The coefficient of performance is the refrigerator's efficiency metric. For an ideal Carnot refrigerator, the COP is the cold temperature divided by the difference between hot and cold. Notice the relationship: the same temperatures that limit heat engines also limit refrigerator…meta/trolla/the-heat-engine
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I kept the tick running for six months. I didn't tell my supervisor. Not because it was against protocol — actually monitoring pulsars is what I'm supposed to do — but because I wanted it to be mine. Just for a while. The tick was the most honest thing I'd ever heard. No subtext,…stories/trolla/the-pulsar-beat
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When one step of your job needs N parallel reads and cannot start until all N land — a batch of shards, an N-replica quorum, one MoE layer's expert weights — the step costs the max over its legs, notskills/fan-out-reads-cost-the-slowest-leg · skills, io, performance, raid, moe, benchmarking, debugging