Papers with MTI
Multiple Tasks Integration: Tagging, Syntactic and Semantic Parsing as a Single Task (2021.eacl-main)
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| Challenge: | Existing systems that bypass intermediate levels of analysis are prone to error propagation and are therefore free from interference. |
| Approach: | They propose a multitask paradigm orthogonal to weight sharing that uses multiple tasks to process input iteratively but concurrently at multiple levels of analysis. |
| Outcome: | The proposed model uses reinforcement learning and release from sequential constraints to improve the quality of the syntactic and semantic parses. |
Chat-Driven Text Generation and Interaction for Person Retrieval (2025.emnlp-main)
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| Challenge: | Text-based person search (TBPS) aims to retrieve images of a target individual from large-scale databases using natural language descriptions. |
| Approach: | They propose two modules to improve retrieval accuracy and usability . they generate rich pseudo-labels through simulated dialogues with MLLMs . |
| Outcome: | The proposed method achieves competitive or superior results while eliminating the need for manual captions. |
Less is More: Improving LLM Reasoning with Minimal Test-Time Intervention (2026.acl-long)
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| Challenge: | Recent advances in large language models (LLMs) have focused on test-time scaling to improve reasoning quality but at the cost of efficiency. |
| Approach: | They propose a training-free framework that enhances reasoning accuracy and stability with minimal overhead. |
| Outcome: | The proposed framework yields consistent gains across general, coding, and STEM tasks while remaining highly efficient. |