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Found 12 papers, 5 papers with code
Improve LLM-as-a-Judge Ability as a General Ability
Furthermore, our training method enhances the general capabilities of the model by constructing complicated judge task, and the judge signals provided by our model have significantly enhanced the downstream DPO training performance of our internal models in our test to optimize policy model with Judge Model.
Yi-Lightning Technical Report
This technical report presents Yi-Lightning, our latest flagship large language model (LLM).
Yi: Open Foundation Models by 01.AI
The Yi model family is based on 6B and 34B pretrained language models, then we extend them to chat models, 200K long context models, depth-upscaled models, and vision-language models.
Ranked #1 on
Chatbot
on AlpacaEval
Supporting Medical Relation Extraction via Causality-Pruned Semantic Dependency Forest
However, the quality of the 1-best dependency tree for medical texts produced by an out-of-domain parser is relatively limited so that the performance of medical relation extraction method may degenerate.
Disentangle and Remerge: Interventional Knowledge Distillation for Few-Shot Object Detection from A Conditional Causal Perspective
To understand the reasons behind this phenomenon, we revisit the learning paradigm of knowledge distillation on the few-shot object detection task from the causal theoretic standpoint, and accordingly, develop a Structural Causal Model.
MME-CRS: Multi-Metric Evaluation Based on Correlation Re-Scaling for Evaluating Open-Domain Dialogue
Firstly, we build an evaluation metric composed of 5 groups of parallel sub-metrics called Multi-Metric Evaluation (MME) to evaluate the quality of dialogue comprehensively.
Multiple Fusion Adaptation: A Strong Framework for Unsupervised Semantic Segmentation Adaptation
MFA basically considers three parallel information fusion strategies, i. e., the cross-model fusion, temporal fusion and a novel online-offline pseudo label fusion.
Cross Modification Attention Based Deliberation Model for Image Captioning
The conventional encoder-decoder framework for image captioning generally adopts a single-pass decoding process, which predicts the target descriptive sentence word by word in temporal order.
MvSR-NAT: Multi-view Subset Regularization for Non-Autoregressive Machine Translation
Conditional masked language models (CMLM) have shown impressive progress in non-autoregressive machine translation (NAT).
PiSLTRc: Position-informed Sign Language Transformer with Content-aware Convolution
Since the superiority of Transformer in learning long-term dependency, the sign language Transformer model achieves remarkable progress in Sign Language Recognition (SLR) and Translation (SLT).
Multi-Scale Local-Temporal Similarity Fusion for Continuous Sign Language Recognition
Continuous sign language recognition (cSLR) is a public significant task that transcribes a sign language video into an ordered gloss sequence.
Infusing Sequential Information into Conditional Masked Translation Model with Self-Review Mechanism
Concretely, we insert a left-to-right mask to the same decoder of CMTM, and then induce it to autoregressively review whether each generated word from CMTM is supposed to be replaced or kept.
