Papers with ZARA
ZARA: Improving Few-Shot Self-Rationalization for Small Language Models (2023.findings-emnlp)
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| Challenge: | Recent studies demonstrate great performance gain for self-rationalization by few-shot prompting LMs with rationale-augmented exemplars. |
| Approach: | They propose to leverage explanations for small LMs to improve few-shot self-rationalization by reducing the problem of plausibility judgement to natural language inference. |
| Outcome: | The proposed approach achieves SOTA performance on the FEB benchmark, for both the task accuracy and the explanation metric. |
ZARA: Training-Free Motion Time-Series Reasoning via Evidence-Grounded LLM Agents (2026.acl-long)
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| Challenge: | Existing approaches to human activity recognition are constrained to fixed activity sets . lack of training-free adaptation to new behavior leads to hallucinations and weak grounding . |
| Approach: | They propose a knowledge- and retrieval-augmented agentic framework for motion time-series reasoning in a training-free inference setting. |
| Outcome: | The proposed framework generalizes robustly to unseen subjects and across datasets . it can be used to train-free inference in a training-free environment . |