HFEPX Archive Slice

HFEPX Daily Archive: 2026-02-28

Updated from current HFEPX corpus (Mar 8, 2026). 27 papers are grouped in this daily page.

Read Full Context

Updated from current HFEPX corpus (Mar 8, 2026). 27 papers are grouped in this daily page. Common evaluation modes: Automatic Metrics. Most common rater population: Domain Experts. Common annotation unit: Multi Dim Rubric. Frequent quality control: Adjudication. Frequently cited benchmark: DROP. Common metric signal: accuracy. Use this page to compare protocol setup, judge behavior, and labeling design decisions before running new eval experiments. Newest paper in this set is from Feb 28, 2026.

Papers: 27 Last published: Feb 28, 2026 Global RSS

Researcher Quick Triage

Use this archive page for time-slice monitoring (what changed in evaluation methods, metrics, and protocol quality this period). Quality band: High .

High-Signal Coverage

100.0%

27 / 27 papers are not low-signal flagged.

Benchmark Anchors

0.0%

Papers with benchmark/dataset mentions in extraction output.

Metric Anchors

11.1%

Papers with reported metric mentions in extraction output.

1 papers report explicit quality controls for this archive period.
Prioritize papers with both benchmark and metric anchors for reliable longitudinal comparisons.

Primary action: Use this slice as early signal only; benchmark/metric anchoring is limited for rigorous period-over-period claims.

Why This Time Slice Matters

11.1% of papers report explicit human-feedback signals, led by rubric ratings.
automatic metrics appears in 11.1% of papers in this hub.
DROP is a recurring benchmark anchor for cross-paper comparisons in this page.

Protocol Takeaways For This Period

Most common quality-control signal is adjudication (3.7% of papers).
Rater context is mostly domain experts, and annotation is commonly multi-dimensional rubrics; use this to scope replication staffing.
Stratify by benchmark (DROP vs C3EBench) before comparing methods.

Start Here (Highest-Signal Papers In This Slice)

Ranked by protocol completeness and evidence density for faster period-over-period review.

Confusion-Aware Rubric Optimization for LLM-based Automated Grading
Feb 28, 2026 · Citations: 0 · Score: 6.0

Eval: Automatic Metrics · Metrics: Accuracy, Precision
SkillCraft: Can LLM Agents Learn to Use Tools Skillfully?
Feb 28, 2026 · Citations: 0 · Score: 5.0

Eval: Automatic Metrics · Metrics: Success rate
BLUFF: Benchmarking the Detection of False and Synthetic Content across 58 Low-Resource Languages
Feb 28, 2026 · Citations: 0 · Score: 5.0

Eval: Automatic Metrics · Metrics: F1
SSKG Hub: An Expert-Guided Platform for LLM-Empowered Sustainability Standards Knowledge Graphs
Feb 28, 2026 · Citations: 0 · Score: 4.5

Eval: Not reported · Metrics: Not reported
Optimizing In-Context Demonstrations for LLM-based Automated Grading
Feb 28, 2026 · Citations: 0 · Score: 3.5

Eval: Not reported · Metrics: Not reported
Piecing Together Cross-Document Coreference Resolution Datasets: Systematic Dataset Analysis and Unification
Feb 28, 2026 · Citations: 0 · Score: 2.5

Eval: Not reported · Metrics: Not reported

Protocol Matrix (Top 10)

Quickly compare method ingredients across this archive slice.

Paper	Eval Modes	Benchmarks	Metrics	Quality Controls
Confusion-Aware Rubric Optimization for LLM-based Automated Grading Feb 28, 2026	Automatic Metrics	Not reported	Accuracy, Precision	Not reported
SkillCraft: Can LLM Agents Learn to Use Tools Skillfully? Feb 28, 2026	Automatic Metrics	Not reported	Success rate	Not reported
BLUFF: Benchmarking the Detection of False and Synthetic Content across 58 Low-Resource Languages Feb 28, 2026	Automatic Metrics	Not reported	F1	Not reported
SSKG Hub: An Expert-Guided Platform for LLM-Empowered Sustainability Standards Knowledge Graphs Feb 28, 2026	Not reported	Not reported	Not reported	Calibration, Adjudication
Optimizing In-Context Demonstrations for LLM-based Automated Grading Feb 28, 2026	Not reported	Not reported	Not reported	Not reported
Piecing Together Cross-Document Coreference Resolution Datasets: Systematic Dataset Analysis and Unification Feb 28, 2026	Not reported	Not reported	Not reported	Not reported
Super Research: Answering Highly Complex Questions with Large Language Models through Super Deep and Super Wide Research Feb 28, 2026	Not reported	Not reported	Not reported	Not reported
Learning Nested Named Entity Recognition from Flat Annotations Feb 28, 2026	Not reported	Not reported	Not reported	Not reported
Constitutional Black-Box Monitoring for Scheming in LLM Agents Feb 28, 2026	Not reported	Not reported	Not reported	Not reported
A Gauge Theory of Superposition: Toward a Sheaf-Theoretic Atlas of Neural Representations Feb 28, 2026	Not reported	Not reported	Not reported	Not reported

Researcher Workflow (Detailed)

Checklist

Gap: Papers with explicit human feedback

Coverage is a replication risk (11.1% vs 45% target).
Gap: Papers reporting quality controls

Coverage is a replication risk (3.7% vs 30% target).
Moderate: Papers naming benchmarks/datasets

Coverage is usable but incomplete (29.6% vs 35% target).
Strong: Papers naming evaluation metrics

Coverage is strong (44.4% vs 35% target).
Gap: Papers with known rater population

Coverage is a replication risk (14.8% vs 35% target).
Gap: Papers with known annotation unit

Coverage is a replication risk (7.4% vs 35% target).

Strengths

This hub still surfaces a concentrated paper set for protocol triage and replication planning.

Known Gaps

Only 3.7% of papers report quality controls; prioritize calibration/adjudication evidence.
Rater population is under-specified (14.8% coverage).
Annotation unit is under-specified (7.4% coverage).

Suggested Next Analyses

Stratify by benchmark (DROP vs C3EBench) before comparing methods.
Track metric sensitivity by reporting both accuracy and agreement.
Add inter-annotator agreement checks when reproducing these protocols.

Recommended Queries

Benchmark Slice: DROP Metric Slice: accuracy Recent High-Signal Papers

Known Limitations

Only 3.7% of papers report quality controls; prioritize calibration/adjudication evidence.
Rater population is under-specified (14.8% coverage).
Narrative synthesis is grounded in metadata and abstracts only; full-paper implementation details are not parsed.

Research Utility Snapshot (Detailed)

Evaluation Modes

Automatic Metrics (3)

Top Metrics

Accuracy (3)
Agreement (2)
F1 (2)
Success rate (2)

Top Benchmarks

DROP (2)
C3EBench (1)
ControlArena (1)
EvoRTL Bench (1)

Quality Controls

Adjudication (1)
Calibration (1)

Papers In This Archive Slice

Learning Nested Named Entity Recognition from Flat Annotations
Igor Rozhkov, Natalia Loukachevitch · Feb 28, 2026 · Citations: 0
Constitutional Black-Box Monitoring for Scheming in LLM Agents
Simon Storf, Rich Barton-Cooper, James Peters-Gill, Marius Hobbhahn · Feb 28, 2026 · Citations: 0
A Gauge Theory of Superposition: Toward a Sheaf-Theoretic Atlas of Neural Representations
Hossein Javidnia · Feb 28, 2026 · Citations: 0
A Comprehensive Evaluation of LLM Unlearning Robustness under Multi-Turn Interaction
Ruihao Pan, Suhang Wang · Feb 28, 2026 · Citations: 0
Qwen3-Coder-Next Technical Report
Ruisheng Cao, Mouxiang Chen, Jiawei Chen, Zeyu Cui, Yunlong Feng · Feb 28, 2026 · Citations: 0
LaSTR: Language-Driven Time-Series Segment Retrieval
Kota Dohi, Harsh Purohit, Tomoya Nishida, Takashi Endo, Yusuke Ohtsubo · Feb 28, 2026 · Citations: 0
RLAR: An Agentic Reward System for Multi-task Reinforcement Learning on Large Language Models
Andrew Zhuoer Feng, Cunxiang Wang, Bosi Wen, Yidong Wang, Yu Luo · Feb 28, 2026 · Citations: 0
SkillCraft: Can LLM Agents Learn to Use Tools Skillfully?
Shiqi Chen, Jingze Gai, Ruochen Zhou, Jinghan Zhang, Tongyao Zhu · Feb 28, 2026 · Citations: 0

Long Horizon

Real-world tool-using agents operate over long-horizon workflows with recurring structure and diverse demands, where effective behavior requires not only invoking atomic tools but also abstracting, and reusing higher-level tool…
DRIV-EX: Counterfactual Explanations for Driving LLMs
Amaia Cardiel, Eloi Zablocki, Elias Ramzi, Eric Gaussier · Feb 28, 2026 · Citations: 0
RAVEL: Reasoning Agents for Validating and Evaluating LLM Text Synthesis
Andrew Zhuoer Feng, Cunxiang Wang, Yu Luo, Bosi Wen, Yidong Wang · Feb 28, 2026 · Citations: 0
Polynomial Mixing for Efficient Self-supervised Speech Encoders
Eva Feillet, Ryan Whetten, David Picard, Alexandre Allauzen · Feb 28, 2026 · Citations: 0
SSKG Hub: An Expert-Guided Platform for LLM-Empowered Sustainability Standards Knowledge Graphs
Chaoyue He, Xin Zhou, Xinjia Yu, Lei Zhang, Yan Zhang · Feb 28, 2026 · Citations: 0

Expert Verification

We present SSKG Hub (Sustainability Standards Knowledge Graph Hub), a research prototype and interactive web platform that transforms standards into auditable knowledge graphs (KGs) through an LLM-centered, expert-guided pipeline.
BLUFF: Benchmarking the Detection of False and Synthetic Content across 58 Low-Resource Languages
Jason Lucas, Matt Murtagh-White, Adaku Uchendu, Ali Al-Lawati, Michiharu Yamashita · Feb 28, 2026 · Citations: 0

Multi Agent

We introduce BLUFF, a comprehensive benchmark for detecting false and synthetic content, spanning 79 languages with over 202K samples, combining human-written fact-checked content (122K+ samples across 57 languages) and LLM-generated…
TraceSIR: A Multi-Agent Framework for Structured Analysis and Reporting of Agentic Execution Traces
Shu-Xun Yang, Cunxiang Wang, Haoke Zhang, Wenbo Yu, Lindong Wu · Feb 28, 2026 · Citations: 0
Piecing Together Cross-Document Coreference Resolution Datasets: Systematic Dataset Analysis and Unification
Anastasia Zhukova, Terry Ruas, Jan Philip Wahle, Bela Gipp · Feb 28, 2026 · Citations: 0

To address these challenges, we introduce uCDCR, a unified dataset that consolidates diverse publicly available English CDCR corpora across various domains into a consistent format, which we analyze with standardized metrics and evaluation…
QQ: A Toolkit for Language Identifiers and Metadata
Wessel Poelman, Yiyi Chen, Miryam de Lhoneux · Feb 28, 2026 · Citations: 0
From Literature to Hypotheses: An AI Co-Scientist System for Biomarker-Guided Drug Combination Hypothesis Generation
Raneen Younis, Suvinava Basak, Lukas Chavez, Zahra Ahmadi · Feb 28, 2026 · Citations: 0
LangGap: Diagnosing and Closing the Language Gap in Vision-Language-Action Models
Yuchen Hou, Lin Zhao · Feb 28, 2026 · Citations: 0
Super Research: Answering Highly Complex Questions with Large Language Models through Super Deep and Super Wide Research
Yubo Dong, Nianhao You, Yuxuan Hou, Zixun Sun, Yue Zhang · Feb 28, 2026 · Citations: 0

Long Horizon

To evaluate this capability, we curated a benchmark of 300 expert-written questions across diverse domains, each requiring up to 100+ retrieval steps and 1,000+ web pages to reconcile conflicting evidence.
Draft-Thinking: Learning Efficient Reasoning in Long Chain-of-Thought LLMs
Jie Cao, Tianwei Lin, Zhenxuan Fan, Bo Yuan, Ziyuan Zhao · Feb 28, 2026 · Citations: 0
CoMoL: Efficient Mixture of LoRA Experts via Dynamic Core Space Merging
Jie Cao, Zhenxuan Fan, Zhuonan Wang, Tianwei Lin, Ziyuan Zhao · Feb 28, 2026 · Citations: 0
CIRCUS: Circuit Consensus under Uncertainty via Stability Ensembles
Swapnil Parekh · Feb 28, 2026 · Citations: 0
Optimizing In-Context Demonstrations for LLM-based Automated Grading
Yucheng Chu, Hang Li, Kaiqi Yang, Yasemin Copur-Gencturk, Kevin Haudek · Feb 28, 2026 · Citations: 0

Rubric RatingDemonstrations

GUIDE paves the way for trusted, scalable assessment systems that align closely with human pedagogical standards.
Confusion-Aware Rubric Optimization for LLM-based Automated Grading
Yucheng Chu, Hang Li, Kaiqi Yang, Yasemin Copur-Gencturk, Joseph Krajcik · Feb 28, 2026 · Citations: 0

Rubric Rating

Empirical evaluations on teacher education and STEM datasets demonstrate that CARO significantly outperforms existing SOTA methods.
RTLocating: Intent-aware RTL Localization for Hardware Design Iteration
Changwen Xing, Yanfeng Lu, Lei Qi, Chenxu Niu, Jie Li · Feb 28, 2026 · Citations: 0
A Typologically Grounded Evaluation Framework for Word Order and Morphology Sensitivity in Multilingual Masked LMs
Anna Feldman, Libby Barak, Jing Peng · Feb 28, 2026 · Citations: 0
LLM-Bootstrapped Targeted Finding Guidance for Factual MLLM-based Medical Report Generation
Cunyuan Yang, Dejuan Song, Xiaotao Pang, Qianqian Shen, Wenjie Nie · Feb 28, 2026 · Citations: 0

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