News / #training Tag Training 500 articles archived under #training · RSS Sign in to follow arXiv — NLP / Computation & Language research 21d ago Transcribe, Translate, and Optimize: Joint Reward Learning for Speech Translation arXiv:2609.26536v1 Announce Type: new Abstract: In LLM-based speech translation, transcription-based chain-of-thought (CoT) suffers from a mismatch between reference transcripts used in supervised fine-tuning (SFT) and model-generated transcripts at inference. To address this,… 24 r/MachineLearning community 22d ago Simulating fault tolerance with stage skipping in pipeline-parallel training [R] Our most recent work at Templar explores fault tolerance in Crucible, our distributed pre-training platform. The goal is to keep healthy workers training when another pipeline stage goes offline. Crucible combines data-parallel replicas with pipeline parallelism. Each replica… 27 The Information — AI news-outlet 22d ago Entertainment-Booking Startup Ande Raises $52 Million From Lightspeed, Redpoint Personal AI agents like Instinct and Muse have promised to take away the hassle of booking hard-to-get restaurant reservations, Broadway tickets and sporting events. Now, a startup is coming out of stealth to do the same for corporate entertainment—events, group dining,… 27 r/LocalLLaMA community 22d ago XiaomiMiMo/MiMo-V2.6-Distill-Qwen-9B https://preview.redd.it/ybwqqbrst0rh1.png?width=811&format=png&auto=webp&s=1e40c5b53e304caf2a10efa2baa6f998b9a9a0bb MiMo-V2.6-Distill-Qwen-9B is a 9B agentic model developed by Xiaomi MiMo through supervised fine-tuning of Qwen3.5-9B on MiMo-generated data. Made by Xiaomi… 38 arXiv — Machine Learning research 22d ago GRRR: The Geometry of Reshaping, Rotation, and Routing in Decoder LLM post-training arXiv:2609.22146v1 Announce Type: new Abstract: We study how post-training changes the weights of Large Language Models (LLMs) relative to their pretrained weights. Across 12 post-training chains with supervised fine-tuning (SFT) and reinforcement learning (RL), we express each… 30 arXiv — Machine Learning research 22d ago A Pinch of SFT, A Dash of RL: When Reinforcement Learning Helps Long-Horizon Advertising Agents arXiv:2609.22194v1 Announce Type: new Abstract: Enterprise analytics agents solve long-horizon tool-use problems over distributed business data, requiring retrieval, reasoning, API calls, code execution, and adaptation to intermediate observations. Supervised fine-tuning (SFT)… 18 arXiv — Machine Learning research 22d ago CAMFT: Conflict-Aware Mergeable Fine-Tuning for Large Language Models arXiv:2609.22253v1 Announce Type: new Abstract: Model merging has emerged as a promising paradigm for integrating multiple task-specific capabilities into a single large language model. However, existing methods predominantly focus on post-hoc processing of independently… 8 arXiv — Machine Learning research 22d ago Strategy Accumulation and Guided Execution for Automated LLM Fine-Tuning arXiv:2609.22257v1 Announce Type: new Abstract: Producing task-specific large language models requires discovering effective training strategies through experimentation. Automated fine-tuning systems have made this experimentation feasible with far less manual effort. However,… 7 arXiv — Machine Learning research 22d ago Prioritized Rollouts for Efficient World Model-based Vision-Language-Action Policy Optimization arXiv:2609.22879v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have emerged as a powerful paradigm for embodied intelligence, but fine-tuning them with reinforcement learning (RL) remains constrained by the cost of real-world robot interaction. Model-based… 38 arXiv — NLP / Computation & Language research 22d ago Evaluating Fine-Tuned and Base Language Models in Maternal and Vaccination Healthcare for African Settings arXiv:2609.22110v1 Announce Type: new Abstract: Background: Large language models (LLMs) can improve healthcare information delivery in low-resource settings but may produce inaccurate or culturally inappropriate advice. This study evaluated domain-specific fine-tuning for… 20 arXiv — NLP / Computation & Language research 22d ago Multilingual Safety Signals Are Multi-Layered: Filtering Safety-Degrading Data for Safer LLMs arXiv:2609.22144v1 Announce Type: new Abstract: Preserving safety alignment during large language models fine-tuning is critical, however, recent studies have demonstrated that even benign fine-tuning data may contain safety-degrading samples that silently undermine safety… 14 arXiv — NLP / Computation & Language research 22d ago Team DArgk at the 2026 ELOQUENT lab for evaluating generative language model quality: Residuals of Humanity: AI Detection Evasion via GRPO Fine-Tuning arXiv:2609.22221v1 Announce Type: new Abstract: Large language models (LLMs) can generate fluent and coherent text that is increasingly difficult to distinguish from human writing, motivating the development of automatic AI-generated text detectors. However, the robustness of… 32 r/LocalLLaMA community 23d ago yandex/AliceAI-Foundation-80B-A3B-Base: Russian-developed competitor to Qwen 35B and DeepSeek V4 Flash https://huggingface.co/yandex/AliceAI-Foundation-80B-A3B-Base It's not a Qwen3 finetune, it's actually its own fully custom architecture. No Llama.cpp support yet sadly (Also note that this model is NOT post-trained like Qwen3.5/3.6)   submitted by   /u/Iwaku_Real [link]… 31 r/LocalLLaMA community 23d ago Hemmingway-1: An AI that writes like a person (Qwen3.8-27B finetune) https://preview.redd.it/d7brwofkhuqh1.png?width=1400&format=png&auto=webp&s=9a0079ebc2710faff9a73378dac58c6dd67e3cec link: https://huggingface.co/Altworld/Hemmingway-1   submitted by   /u/paf1138 [link]   [comments] 5 arXiv — NLP / Computation & Language research 23d ago Prediction Dynamics in Depth-Recurrent Language Models arXiv:2609.21383v1 Announce Type: new Abstract: Depth-recurrent language models refine predictions through repeated latent updates. Why can intermediate answers agree with the endpoint while their scores continue to change? We derive a sharp margin characterization that… 4 arXiv — NLP / Computation & Language research 23d ago Cross-Lingual Parkinson's Disease Severity Assessment Using Pre-trained Speech Embeddings: A Multi-Class Evaluation arXiv:2609.20875v1 Announce Type: cross Abstract: Parkinson's disease (PD) often manifests through speech impairments, facilitating accessible, non-invasive, and cost-effective severity assessment for early diagnosis and progression tracking. Despite advances in speech… 31 arXiv — NLP / Computation & Language research 23d ago Cultural Alignment in Large Language Models Using Soft Prompt Tuning arXiv:2503.16094v2 Announce Type: replace Abstract: Large Language Model (LLM) alignment is commonly achieved through supervised fine-tuning or reinforcement learning, both of which require labeled or preference data and update model weights. Without targeted cultural… 4 r/LocalLLaMA community 24d ago I gave Jev, Laya, finetuned ModernCE and Qwen3.5 the controls to Doom I gave Jev, Laya, a finetuned ModernCE-base-nli and a finetuned Qwen3.5-4B the controls to Doom. Thanks to TypeSafe AI for Jev access. The video lines up the starts of four separate games with the same seed. After that, each model's actions change its own game and what it sees… 30 OpenAI Python SDK releases dev-tools 26d ago v3.16.0 3.16.0 (2026-09-18) Features api: add webhook endpoint management ( #3892 ) ( 9a11f6e ) Chores api: deprecate MCP connector_id ( #3894 ) ( 1ccaf07 ) 26 arXiv — Machine Learning research 26d ago CellRFT: Reinforcement Fine-Tuning for Single-Cell Perturbation Modeling arXiv:2609.19970v1 Announce Type: new Abstract: Predicting cellular responses to perturbations supports the study of gene function, disease mechanisms, and therapeutic strategies. Despite advances in single-cell perturbation modeling, existing models typically optimize surrogate… 27 arXiv — Machine Learning research 26d ago Past, Future, All at Once: Mitigating Stability-Plasticity Dilemma via Post-hoc JANUS Rectification arXiv:2609.19985v1 Announce Type: new Abstract: Fine-tuning foundation models on new tasks inevitably suffer from catastrophic forgetting. While existing works attempt to mitigate this on the basis of parameter-efficient fine-tuning methods, they adopted an overly restrictive… 28 arXiv — NLP / Computation & Language research 26d ago Neo-Classic: A Benchmark for Evaluating Linguistic-Aesthetic Reasoning in Classical Chinese Poetry arXiv:2609.19154v1 Announce Type: new Abstract: While Large Language Models (LLMs) achieve high accuracy on established Classical Chinese Poetry benchmarks, it remains challenging to distinguish transferable Linguistic-Aesthetic Reasoning from reliance on familiar pre-training… 4 arXiv — NLP / Computation & Language research 26d ago Reflective Recovery: A Self-Supervised Method for Reasoning by Learning from Mistakes arXiv:2609.19156v1 Announce Type: new Abstract: Data-driven fine-tuning is widely adopted to enhance reasoning in Large Language Models (LLMs) due to its simplicity and efficiency. However, mainstream imitation learning methods that rely exclusively on perfect reasoning… 30 arXiv — NLP / Computation & Language research 26d ago Fine-Tuning Models for Biomedical Relation Extraction arXiv:2609.20169v1 Announce Type: new Abstract: Next-Generation Sequencing has revolutionized the study of genetic mutations, enabling large-scale investigations into their roles in disease development. However, extracting meaningful insights from the vast amount of biomedical… 7 arXiv — NLP / Computation & Language research 26d ago Riemannian--Lorentz Fusion of Vision Transformers and State-Space Models arXiv:2609.19384v1 Announce Type: cross Abstract: Scaling deep learning faces critical bottlenecks: data exhaustion, exponential training costs, and resource concentration. Model merging combines pre-trained checkpoints without gradient descent, offering orders-of-magnitude… 5 arXiv — NLP / Computation & Language research 26d ago AutoData: Agentic Search for Pre-training Data Selection arXiv:2609.19754v1 Announce Type: cross Abstract: LLM agents have recently shown promise in automating machine learning engineering by editing model and training code under execution feedback. Data, however, remains largely outside this agentic optimisation loop. We frame… 20 r/LocalLLaMA community 27d ago Thank you :) Swift Qwen 3.8 27B now has 100k+ downloads, is #1 finetune and #9 model on HuggingFace Trending Hey everyone, Jovan from UkisAI here, a small lab building the tech to make tiny frontier LLMs possible (and doing it open-source!) The purpose of this post is simply to thank the community for all the amazing finetunes, quantizations and overall improvements over our original… 38 Hugging Face Daily Papers research 27d ago CERA-MoA: Co-Evolving Routing Mechanisms with Continually Learning LLM Agents Abstract Current Mixture-of-Agents (MoA) paradigms generally treat query routing and agent fine-tuning as separate processes, limiting their ability to respond to evolving agent capabilities. This disconnect prevents routing strategies from adapting to evolving agent… 20 arXiv — Machine Learning research 27d ago Pay Only for Disagreement: Certified No-Regression Verdicts for Model Updates with Matching Label-Complexity Bounds arXiv:2609.17560v1 Announce Type: new Abstract: Every production model is updated, by retraining, fine-tuning, quantization, or a silent vendor swap, and each update risks being worse than what it replaced. We formalize update promotion as certified paired risk-difference… 26 arXiv — Machine Learning research 27d ago Hybrid coupling with numerics-informed neural networks and the overlapping Schwarz alternating method arXiv:2609.17841v1 Announce Type: new Abstract: We develop a hybrid modeling framework for coupling pre-trained numerics-informed neural networks (NINNs) with classical full order models (FOMs) using the overlapping Schwarz alternating method. We consider the two-dimensional… 34 arXiv — Machine Learning research 27d ago Dataset-Dependent Effects of Cross-Depth Aggregation and Soft-Routed Experts in EEG Foundation Model Fine-Tuning arXiv:2609.17886v1 Announce Type: new Abstract: EEG decoding tasks can rely on different temporal dynamics and cross-channel relationships. We test whether specialized modules improve a fully fine-tuned EEG foundation model by augmenting CBraMod with cross-depth Attention… 9 arXiv — Machine Learning research 27d ago Spatially Adaptive Noise Injection arXiv:2609.18466v1 Announce Type: new Abstract: Diffusion samplers reverse a learned noising process using either stochastic (DDPM) or deterministic (DDIM) updates, which represent endpoints of a single family controlled by a scalar noise-injection variance that is applied… 5 arXiv — NLP / Computation & Language research 27d ago SFT or RL for Tool-Calling Agents? A Controlled Study Across Data, Method, and Scale arXiv:2609.17848v1 Announce Type: new Abstract: Limited controlled evidence exists on how training data, adaptation method, and model scale jointly affect tool-calling performance in language-model agents. We evaluate supervised fine-tuning (SFT) with LoRA, reinforcement… 34 arXiv — NLP / Computation & Language research 27d ago Dependency-Aware Trajectory Refinement for Efficient Multi-Turn Agent Fine-Tuning arXiv:2609.18417v1 Announce Type: new Abstract: Multi-turn agent trajectories often contain redundant rounds (failed tool calls, parallel sub-queries, verification-only steps) that inflate both training and inference cost. We propose viewing each trajectory as a… 15 arXiv — NLP / Computation & Language research 27d ago WordPolo: Evaluating Language Models Through Iterative Semantic Feedback arXiv:2609.19006v1 Announce Type: new Abstract: Large Language Models (LLMs) and Large Reasoning Models (LRMs) are typically evaluated on challenging benchmarks through dataset accuracy alone, providing no insight into the quality or faithfulness of their reasoning processes. We… 23 arXiv — NLP / Computation & Language research 27d ago Encoder Awakening via Adapters: Effective Domain-Adaptive Fine-tuning of Speech-LLMs arXiv:2609.17981v1 Announce Type: cross Abstract: Speech Large Language Models (Speech-LLMs), typically built from a pre-trained speech encoder, a modality projector, and an LLM fine-tuned with Low-Rank Adapters (LoRA), have shown strong Automatic Speech Recognition (ASR)… 32 arXiv — NLP / Computation & Language research 28d ago POSPAN: Position-Constrained Span Masking for Language Model Pre-training arXiv:2609.16061v1 Announce Type: cross Abstract: Span-level masked language modeling (MLM) has shown to be advantageous to pre-trained language models over the original single-token MLM, as entities/phrases and their dependencies are critical to language understanding. Previous… 17 arXiv — Machine Learning research 28d ago Efficient Reasoning Distillation: Small Video-Language Models via Synthetic CoT and Difficulty-Aware Fine-Tuning arXiv:2609.16255v1 Announce Type: new Abstract: We present an efficient method to distill reasoning capabilities into compact video-language models (VLMs) for video question answering (VideoQA). Our approach fine-tunes a 2B-parameter model using only $\sim$900… 21 arXiv — NLP / Computation & Language research 28d ago TAME: Token Attribution and Masking for Emergent misalignment arXiv:2609.16754v1 Announce Type: cross Abstract: Fine-tuning an aligned language model on narrow, flawed data can induce harmful behavior far outside the training domain, known as emergent misalignment (EM). Prior work has localized EM in model weights, activations, and… 6 arXiv — NLP / Computation & Language research 28d ago Nepali Legal Expertise through Generative and Extractive Pre-trained Transformers (NepLEGiT) arXiv:2609.16010v1 Announce Type: new Abstract: The complexity of legal language and limited accessibility to legal information pose significant challenges to justice delivery in Nepal. Traditional legal services remain inaccessible to many citizens due to language barriers,… 25 arXiv — NLP / Computation & Language research 28d ago Retrieval-Driven Memory Reconsolidation for Long-Term LLM Agents arXiv:2609.16053v1 Announce Type: new Abstract: Long-term memory is essential for LLM-based agents operating over extended interactions. Existing memory systems primarily update memory when new information arrives, treating retrieval as the endpoint of memory access rather than… 6 arXiv — NLP / Computation & Language research 28d ago Towards Scalable RLVR: Multimodal Instruction Following Data Synthesis and Distillation arXiv:2609.16059v1 Announce Type: new Abstract: Multimodal instruction following (MMIF) is crucial for building generalist agents. However, current training paradigms rely heavily on Supervised Fine-Tuning (SFT), which often leads to surface-level pattern matching and degrades… 22 arXiv — NLP / Computation & Language research 28d ago ReMova: Fine-tuning LLMs for English to Belarusian translation arXiv:2609.16427v1 Announce Type: new Abstract: This paper presents a Belarusian-specific data-cleaning pipeline and fine-tuning for English-Belarusian machine translation. Our cleaning pipeline distinguishes itself from others by employing a correction tool that addresses the… 4 arXiv — NLP / Computation & Language research 28d ago Style-Debiased DPO: Updating LLM Knowledge with Factuality-Aware Synthetic Preference Data arXiv:2609.16532v1 Announce Type: new Abstract: Continued pretraining (CPT) with data augmentation such as paraphrasing can store inside a large language model (LLM) the knowledge of a small source corpus. The stored knowledge, however, is not always retrieved correctly. We… 10 arXiv — NLP / Computation & Language research 28d ago DiaWhisper-DPO: Role-Attributed Transcription of Clinical Interviews via Failure-Mined Preference Optimization arXiv:2609.16661v1 Announce Type: new Abstract: Automated depression screening from clinical interviews requires attribution of utterances to the clinician or patient. We evaluate two datasets: DAIC-WOZ, where participant-only recordings require re-synthesizing both sides for… 18 arXiv — NLP / Computation & Language research 28d ago Where Should a Document Live: Context, Representations, or Parameters? arXiv:2609.17346v1 Announce Type: new Abstract: To answer questions outside of their pre-training data, large language models (LLMs) need access to new information, which can be presented in the context window as documents, encoded into the model's parameters, or injected as… 21 arXiv — NLP / Computation & Language research 28d ago LSREP: A Longitudinal State-Replay Protocol for Evaluating Conversational Memory, with ICE v2 as an Audited Local-First Architecture arXiv:2609.16730v1 Announce Type: cross Abstract: Conversational memory changes during use, so endpoint question answering alone cannot establish how a persistent state accumulates, ages, or incorporates revisions. We introduce LSREP, a Longitudinal State-Replay Evaluation… 33 OpenAI Python SDK releases dev-tools 28d ago v3.14.1 3.14.1 (2026-09-15) Bug Fixes client: validate retry limits and preserve application errors ( #3867 ) ( f86c721 ) correct typo "th" to "the" in StreamAlreadyConsumed error message ( #3022 ) ( 7186203 ) examples: correct Azure endpoint hostname ( #3298 ) ( 543516c ) examples:… 16 arXiv — Machine Learning research 29d ago Task-Aware Federated Fine-Tuning for MoE-based Large Language Models arXiv:2609.13395v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) has become a widely adopted architecture for Large Language Models (LLMs), as it improves model capacity while limiting computational overhead through sparse expert activation. This property makes MoE-based… 26 arXiv — Machine Learning research 29d ago Adaptive Phase-Switching for Communication-Efficient Federated LoRA Fine-Tuning arXiv:2609.13512v1 Announce Type: new Abstract: Federated fine-tuning of large language models with low-rank adaptation reduces per-client trainable parameters, but client-to-server communication remains the dominant cost. Existing accounting for federated LoRA protocols omits… 10 Page 3 of 10 · 500 articles ← Newer Older →
