Zuhong Lin, Daoyuan Ren, Kai Ran, Jing Sun, Songlin Yu, Xuefeng Bai · Apr 26, 2025 · Citations: 0
Automatic Metrics Coding
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← Back to explorer Reshaping MOFs text mining with a dynamic multi-agents framework of large language model Diffusion Generative Recommendation with Continuous Tokens Overcoming Sparsity Artifacts in Crosscoders to Interpret Chat-Tuning Moving Beyond Medical Exams: A Clinician-Annotated Fairness Dataset of Real-World Tasks and Ambiguity in Mental Healthcare Oracular Programming: A Modular Foundation for Building LLM-Enabled Software
Tag: Coding
Involves software engineering or code-quality expertise.
Papers in tag: 314
Research Utility Snapshot
Evaluation Modes
- Automatic Metrics (5)
Human Feedback Types
- Pairwise Preference (3)
- Demonstrations (1)
- Expert Verification (1)
Required Expertise
- Coding (5)
- Medicine (1)
Haohao Qu, Shanru Lin, Yujuan Ding, Yiqi Wang, Wenqi Fan · Apr 16, 2025 · Citations: 0
Pairwise Preference Automatic Metrics Coding
- Specifically, ContRec consists of two key modules: a sigma-VAE Tokenizer, which encodes users/items with continuous tokens; and a Dispersive Diffusion module, which captures implicit user preference.
- By conditioning on the previously generated tokens of the LLM backbone during user modeling, the Dispersive Diffusion module performs a conditional diffusion process with a novel Dispersive Loss, enabling high-quality user preference genera
Julian Minder, Clément Dumas, Caden Juang, Bilal Chugtai, Neel Nanda · Apr 3, 2025 · Citations: 0
Pairwise Preference Automatic Metrics Coding
- Using the BatchTopK crosscoder, we successfully identify a set of chat-specific latents that are both interpretable and causally effective, representing concepts such as $\textit{false information}$ and $\textit{personal question}$, along w
Max Lamparth, Declan Grabb, Amy Franks, Scott Gershan, Kaitlyn N. Kunstman, Aaron Lulla · Feb 22, 2025 · Citations: 0
Pairwise PreferenceExpert Verification Automatic Metrics MedicineCoding
- Current medical language model (LM) benchmarks often over-simplify the complexities of day-to-day clinical practice tasks and instead rely on evaluating LMs on multiple-choice board exam questions.
- This design enables systematic evaluations of model performance and bias by studying how demographic factors affect decision-making.
Jonathan Laurent, André Platzer · Feb 7, 2025 · Citations: 0
Demonstrations Automatic Metrics Coding