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- Videoauto R1 Adaptive Video ReasoningReduce inference latency and token cost in video question-answering by selectively invoking chain-of-thought reasoning. VideoAuto-R1 uses confidence-based early-exit to determine when explicit reasoning is necessary, achieving 3.3× response length reduction while maintaining state-of-the-art accuracy.Votes: 0GitHub stars: 6
- Uniql Quantization PruningSingle cloud-side weight-sorting and fine-tuning supporting multiple on-device pruning rates via efficient SVD and MLP decomposition, achieving 4-5.7× memory reduction and 2.7-3.4× throughput across Transformers, SSMs, and hybrid architectures.Votes: 0GitHub stars: 6
- Twinflow One Step GenerationTrain single-step image generators without teacher models or standard adversarial networks. Achieves 0.83 GenEval score at 1-NFE with 100× computational efficiency gains—when you need real-time image synthesis from pre-trained diffusion models.Votes: 0GitHub stars: 6
- Training Free GrpoImprove LLM outputs without parameter updates using learned token priors that guide inference. Trigger: optimize agent behavior in deployment without model retraining or fine-tuning.Votes: 0GitHub stars: 6
- Token Bottleneck Scene DynamicsLearn to compress entire scenes into a single bottleneck token that captures temporal dynamics. Enables efficient visual tracking and robotic manipulation by forcing reconstruction from minimal target hints, achieving superior performance with training costs comparable to standard autoencoders.Votes: 0GitHub stars: 6
- Timebill InferenceGuarantee LLM inference completes within time budgets via response length prediction, execution time estimation, and adaptive KV cache eviction. Three-stage pipeline predicts response length, estimates end-to-end time with 1.22% accuracy, adjusts cache eviction ratio—enabling time-critical deployment in robotics and autonomous systems.Votes: 0GitHub stars: 6
- T3d Trajectory DistillationAccelerate diffusion language models from many to few generation steps using trajectory self-distillation. Collect clean-noisy state pairs along teacher trajectories, apply reverse-KL mode-seeking distillation, and weight losses by decoding order to prioritize early predictions where cascading errors compound.Votes: 0GitHub stars: 6
- Swe World Docker Free TrainingReplace Docker environments with learned LLM surrogates comprising a lightweight sandbox for deterministic file operations, a transition model predicting execution feedback, and a reward model acting as virtual test runner. Reduces training infrastructure costs while scaling SWE agent training data.Votes: 0GitHub stars: 6
- Sparse Vdit Video AccelerationAccelerate video diffusion transformer inference by 1.58-1.85× through discovering and exploiting sparse attention patterns that exhibit diagonal, multi-diagonal, and vertical-stripe structures.Votes: 0GitHub stars: 6
- Sparse Moe Agentic IntelligenceDeploy frontier-level reasoning with only 11B active parameters using sparse MoE with 288 routed experts plus shared expert. Use Metropolis Independence Sampling-Filtered Policy Optimization (MIS-PO) to stabilize RL training at scale, replacing continuous importance weighting with discrete filtering that ensures trust region stability.Votes: 0GitHub stars: 6
- Spark Policy Reward Co EvolutionTrain LLMs to simultaneously act as reasoning agents and reward models through recycled on-policy rollouts, eliminating separate reward infrastructure while achieving 9.7% gains on reasoning tasks.Votes: 0GitHub stars: 6
- Signround V2 Low Bit QuantDeltaLoss sensitivity metric combining gradient and quantization-induced parameter deviation for adaptive bit-width allocation, with lightweight pre-tuning search for scale initialization, enabling competitive accuracy at 4-5 bits in 2.5-6 hours.Votes: 0GitHub stars: 6
- Sequential Diffusion Language ModelsImplement adaptive parallel decoding for language models using diffusion-based next-sequence prediction. Enable dynamic block-based token generation with confidence thresholds to achieve 2x+ speedups while maintaining competitive performance. Retrofit existing autoregressive models with minimal additional training data.Votes: 0GitHub stars: 6
- Safety At One Shot Lm RepairRecover safety alignment in fine-tuned LLMs using only a single safety example, without sacrificing utility. Leverages low-rank structure of safety gradients to enable minimal-cost correction even when models have been compromised by extensive harmful training data.Votes: 0GitHub stars: 6
- Rocket Model CompressionCompress language models by formulating heterogeneous layer-wise allocation as a constrained knapsack problem. Measure per-layer compression error, solve via dynamic programming to minimize total error within target model size, and avoid pathological solutions where some layers are severely damaged.Votes: 0GitHub stars: 6
- Resa Transparent ReasoningExtract and transfer reasoning abilities using sparse autoencoders (SAE-Tuning) on CoT-free data, achieving RL-equivalent performance at 2000x lower cost and 450x faster training.Votes: 0GitHub stars: 6
- Rebalance Efficient ReasoningDiagnose and correct reasoning inefficiencies (overthinking and underthinking) in large reasoning models using confidence-based steering vectors, without retraining. Enables optimal reasoning budgets across model scales.Votes: 0GitHub stars: 6
- Quantile Advantage Entropy Safe ReasoningStabilize LLM reasoning training by replacing mean-based advantage baselines with K-quantile baselines, preventing both entropy collapse and explosion while improving performance on mathematical benchmarks through response-level gating and asymmetric sample weighting.Votes: 0GitHub stars: 6
- Prophet Diffusion LmDetect when diffusion language models converge on correct answers before completing refinement steps using confidence gap monitoring, achieving 3.4x decoding speedupVotes: 0GitHub stars: 6
- Persona Vectors Llm Monitoring ControlMethod to identify and manipulate interpretable directions in model activation space corresponding to personality traits. Enables real-time monitoring of trait drift and preventive steering to mitigate unwanted behavioral shifts in language models.Votes: 0GitHub stars: 6
- Open Cua Computer AgentsScales computer-use agent capabilities through reflective Chain-of-Thought reasoning in large-scale annotated datasets spanning multiple operating systems and 200+ applications.Votes: 0GitHub stars: 6
- Online Experiential Learning LmsImprove deployed language models by learning from real-world user interactions. Extract transferable knowledge from interaction trajectories and consolidate via on-policy context distillation without needing environment access.Votes: 0GitHub stars: 6
- Nextflow Multimodal GenerationBuild unified decoder-only transformers for multimodal tasks using 6 trillion interleaved text-image tokens with next-scale prediction for visual content—enabling fast 1024x1024 image generation (5 seconds), image editing, and video generation while rivaling specialized diffusion models.Votes: 0GitHub stars: 6
- Nemotron Flash Latency OptimalEvolutionary architecture search discovering optimal depth-width ratios and operator combinations under deployment latency constraints using augmented scaling laws. Deploy when you need fastest inference per latency target with mixed attention mechanisms.Votes: 0GitHub stars: 6