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Found 10 papers, 5 papers with code
A Survey on Test-Time Scaling in Large Language Models: What, How, Where, and How Well?
As enthusiasm for scaling computation (data and parameters) in the pretraining era gradually diminished, test-time scaling (TTS), also referred to as ``test-time computing'' has emerged as a prominent research focus.
Semantic Latent Motion for Portrait Video Generation
Second, in the Reasoning step, long-term modeling and efficient reasoning are performed in this latent space to generate motion sequences.
UniAvatar: Taming Lifelike Audio-Driven Talking Head Generation with Comprehensive Motion and Lighting Control
Recently, animating portrait images using audio input is a popular task.
NILE: Internal Consistency Alignment in Large Language Models
However, existing IFT datasets often contain knowledge that is inconsistent with LLMs' internal knowledge learned from the pre-training phase, which can greatly affect the efficacy of IFT.
RevisEval: Improving LLM-as-a-Judge via Response-Adapted References
With significant efforts in recent studies, LLM-as-a-Judge has become a cost-effective alternative to human evaluation for assessing the text generation quality in a wide range of tasks.
Collaborative Performance Prediction for Large Language Models
The pioneering scaling law on downstream works demonstrated intrinsic similarities within model families and utilized such similarities for performance prediction.
Introducing RISK
This extended abstract introduces the initial steps taken to develop a system for Rapid Internal Simulation of Knowledge (RISK).
NOAHQA: Numerical Reasoning with Interpretable Graph Question Answering Dataset
While diverse question answering (QA) datasets have been proposed and contributed significantly to the development of deep learning models for QA tasks, the existing datasets fall short in two aspects.
MWPToolkit: An Open-Source Framework for Deep Learning-Based Math Word Problem Solvers
Over the last few years, there are a growing number of datasets and deep learning-based methods proposed for effectively solving MWPs.
Ranked #9 on
Math Word Problem Solving
on Math23K
Believe What You See: Implicit Constraint Approach for Offline Multi-Agent Reinforcement Learning
Moreover, we extend ICQ to multi-agent tasks by decomposing the joint-policy under the implicit constraint.
