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Open-access proceedings for conferences, workshops and symposia. Organisers deposit their accepted papers; every paper and every volume receives a DOI.
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We measure energy per generated token for eleven small language models on three mobile systems-on-chip. Memory traffic, not arithmetic, explains most of the variation, and the best configuration per device differs by up to 2.4×.
Priya Venkataraman, Anders Holm
Personalising a model on a user's device requires small, fast-to-train updates. We study rank, placement and quantisation of low-rank adapters on a phone-class model and find that rank 4 on attention projections gives most of the gain at under 2 MB per user.
A poster summarising latency, memory and quality for twenty sub-billion-parameter models on a laptop CPU, a single-board computer and a mobile phone.
Agents that retry failed tool calls recover from transient errors but can also compound mistakes and waste resources. We analyse 18,000 recorded agent runs and show that retries help for network and rate-limit errors but hurt for malformed arguments. We propose a retry budget that depends on the error class and show that it improves success by 6 points at equal cost.
Tool-using agents are typically granted broad credentials, so a single injected instruction can cause large harm. We describe a capability-token scheme in which every tool call carries a narrowly scoped, short-lived token issued by a policy layer outside the model. A prototype blocks all 41 attack scripts in our test suite with under 4 ms of added latency.
Some tool failures return plausible but wrong output and raise no error. We detect such silent failures by comparing the distribution of tool outputs against a rolling reference and flagging shifts. On three deployed tools the detector finds 71% of injected faults with a 2% false-alarm rate.
Sofia Lindqvist, Julia Fernandes
Auditing an agent requires knowing what it saw, decided and did. We propose a small, open logging schema with eleven required fields, and show that it is sufficient to reconstruct the action sequence for 96% of runs in a sample of public agent traces. The schema is published under CC0.
We report experience building perturbation suites — rephrased instructions, reordered tool lists, noisy outputs — for three deployed agents, and summarise which perturbations revealed real failures and which only added cost.
