🤗 PEFT welcomes new merging methods

The N Implementation Details of RLHF with PPO

Operational Identity: A Finite Audit of Declared and Implemented Rules of Sameness

arXiv:2607. 20729v1 Announce Type: cross Abstract: A record system declares when two records refer to the same entity, occurrence, scope, or rule.

CORAM: Coherent Orthogonal Rotation for Model Merging

arXiv:2608. 17366v1 Announce Type: new Abstract: Merging finetuned models combines specialized capabilities without joint training or access to the original data.

Case study: solving P-99 with LPTP and an LLM

arXiv:2607. 21196v1 Announce Type: cross Abstract: Ninety-Nine Prolog Problems (P-99) is a famous set of Prolog exercises.

When Model Merging Rivals Joint Multi-Task Reinforcement Learning: A Task-Vector Geometry Analysis

arXiv:2607. 16062v1 Announce Type: cross Abstract: Model merging is promoted as a substitute for joint multi-task training, yet in the reinforcement-learning setting this substitution is essentially never tested against the baseline it claims to replace: methods merge independently released agents precisely because a joint model is unavailable.

CORAM: Coherent Orthogonal Rotation for Model Merging

Merging finetuned models combines specialized capabilities without joint training or access to the original data. Most methods operate by linear arithmetic in Euclidean weight space, which cannot carry the geometry of the update.

Predicting Mergeability of Parameter-Efficient Fine-Tuning Updates

arXiv:2606. 19549v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) makes it cheap to train many domain- and task-specific language model adapters, but whether two adapters can be merged is usually discovered only after both have been fully trained and evaluated.

Surrogate Benchmarks for Model Merging Optimization

arXiv:2509. 02555v2 Announce Type: replace-cross Abstract: Model merging techniques aim to integrate the abilities of multiple models into a single model.

Sorries Are Not the Hard Part: An Expert-Review Case Study of a Semi-Autonomous Formalization

arXiv:2606. 13925v1 Announce Type: new Abstract: Large language models can often close proof gaps in interactive theorem provers, but a verified theorem is not the same thing as a reusable library contribution.

AGM-like Paraconsistent Partial Meet Abductive Expansion Operation

arXiv:2607. 09729v1 Announce Type: new Abstract: In his 1996 doctoral thesis, Maurice Pagnucco created the first AGM-like abductive expansion operation.

Rethinking Heterogeneous LLM Merging: A Weighted Model Averaging Perspective

arXiv:2607. 18026v1 Announce Type: new Abstract: Can large language models with substantially different parameter spaces be merged by direct weighted averaging, without training or semantic alignment?

Theory-Level Autoformalization: From Isolated Statements to Unified Formal Knowledge Bases

arXiv:2607. 13292v1 Announce Type: new Abstract: Autoformalization translates informal natural language into formal, machine-verifiable languages.